When they are flying,Great evening bat ( Ia io ) produces short FM echolocation calls including three harmonics,of which the first one and the second one are stronger.As they fly,the first harmonic is modulated from 4...When they are flying,Great evening bat ( Ia io ) produces short FM echolocation calls including three harmonics,of which the first one and the second one are stronger.As they fly,the first harmonic is modulated from 49 0 to 18 3 kHz,the second one is modulated from 80 0 to 35 6 kHz,and the third one from 87 2 to 56 7 kHz.The average duration of the calls is 3 7 ms.It was predicted that Great evening bat ( Ia io ) captures big insects in the open area among foliages according to the sound characteristic analysis of echolocation calls and the analysis comparing with the echolocation calls of other bats that perch in the same cave.展开更多
Bats account for 30% of mammal diversity in SE Asia and are potential bioindicators of wider biodiversity impacts resulting from habitat loss and climate change. As existing sampling techniques in the region typically...Bats account for 30% of mammal diversity in SE Asia and are potential bioindicators of wider biodiversity impacts resulting from habitat loss and climate change. As existing sampling techniques in the region typically fail to record bats that habitually fly in open areas and at higher altitudes, current inventory efforts are less than comprehensive. Acoustic sampling with bat detectors may help to overcome these limitations for insectivorous bats, but has yet to be tested in mainland SE Asia. To do so, we sampled bats while simultaneously recording the echolocation calls of insectivorous species commuting and foraging in a variety of karst habitats in north Vietnam. Monitoring of cave-dwelling bats was also undertaken. Discriminant function analysis of 367 echolocation calls produced by 30 insectivorous species showed that acoustic identification was feasible by correctly classifying 89. 1% of calls. In all habitats, acoustic sampling and capture methods recorded significantly more species each night than capture methods alone. Capture methods consequently failed to record 29% （ten spp. of aerial insectivores） of the bat fauna in commuting and foraging habitats and 11% （two spp. ） of that in our cave sample. Only four of these species were subsequently captured following significantly greater sampling effort. This strongly suggests that acoustic methods are indispensable for maximizing bat inventory completeness in SE Asia. As accurate inventories and monitoring are essential for effective species conservation, we recommend the inclusion of acoustic sampling in future studies of bat assemblages across the region [ Current Zoology 55 （5） ： 327 - 341, 2009].展开更多
Previous studies indicated that fruit bats carry two betacoronaviruses,BatCoV HKU9 and BatCoV GCCDC1.To investigate the epidemiology and genetic diversity of these coronaviruses,we conducted a longitudinal surveillanc...Previous studies indicated that fruit bats carry two betacoronaviruses,BatCoV HKU9 and BatCoV GCCDC1.To investigate the epidemiology and genetic diversity of these coronaviruses,we conducted a longitudinal surveillance in fruit bats in Yunnan province,China during 2009–2016.A total of 59(10.63%)bat samples were positive for the two betacorona-viruses,46(8.29%)for HKU9 and 13(2.34%)for GCCDC1,or closely related viruses.We identified a novel HKU9 strain,tentatively designated as BatCoV HKU9-2202,by sequencing the full-length genome.The BatCoV HKU9-2202 shared 83%nucleotide identity with other BatCoV HKU9 stains based on whole genome sequences.The most divergent region is in the spike protein,which only shares 68%amino acid identity with BatCoV HKU9.Quantitative PCR revealed that the intestine was the primary infection organ of BatCoV HKU9 and GCCDC1,but some HKU9 was also detected in the heart,kidney,and lung tissues of bats.This study highlights the importance of virus surveillance in natural reservoirs and emphasizes the need for preparedness against the potential spill-over of these viruses to local residents living near bat caves.展开更多
We tested the prediction that at coarse spatial scales, variables associated with climate, energy, and productivity hy- potheses should be better predictor（s） of bat species richness than those associated with envir...We tested the prediction that at coarse spatial scales, variables associated with climate, energy, and productivity hy- potheses should be better predictor（s） of bat species richness than those associated with environmental heterogeneity. Distribution ranges of 64 bat species were estimated with niche-based models informed by 3629 verified museum specimens. The influence of environmental correlates on bat richness was assessed using ordinary least squares regression （OLS）, simultaneous autoregressive models （SAR）, conditional autoregressive models （CAR）, spatial eigenvector-based filtering models （SEVM）, and Classification and Regression Trees （CART）. To test the assumption of stationarity, Geographically Weighted Regression （GWR） was used. Bat species richness was highest in the eastern parts of southern Africa, particularly in central Zimbabwe and along the western border of Mozambique. We found support for the predictions of both the habitat heterogeneity and climate/productivity/energy hypothe- ses, and as we expected, support varied among bat families and model selection. Richness patterns and predictors of Miniopteridae and Pteropodidae clearly differed from those of other bat families. Altitude range was the only independent variable that was sig- nificant in all models and it was most often the best predictor of bat richness. Standard coefficients of SAR and CAR models were similar to those of OLS models, while those of SEVM models differed. Although GWR indicated that the assumption of stationa- rity was violated, the CART analysis corroborated the findings of the curve-fitting models. Our results identify where additional data on current species ranges, and future conservation action and ecological work are needed.展开更多
文摘When they are flying,Great evening bat ( Ia io ) produces short FM echolocation calls including three harmonics,of which the first one and the second one are stronger.As they fly,the first harmonic is modulated from 49 0 to 18 3 kHz,the second one is modulated from 80 0 to 35 6 kHz,and the third one from 87 2 to 56 7 kHz.The average duration of the calls is 3 7 ms.It was predicted that Great evening bat ( Ia io ) captures big insects in the open area among foliages according to the sound characteristic analysis of echolocation calls and the analysis comparing with the echolocation calls of other bats that perch in the same cave.
基金Lam Quang Oanh and Nguyen Tien Dung of Kim Hy Nature Reserve,Nong The Dzien and Bui Van Dinh of Ba Be National Park and Trieu Van Luc of Bac Kan Provincial Forest Protection Department for arranging research permissions(No.317/UBND-NVand631/UBND-NV)
文摘Bats account for 30% of mammal diversity in SE Asia and are potential bioindicators of wider biodiversity impacts resulting from habitat loss and climate change. As existing sampling techniques in the region typically fail to record bats that habitually fly in open areas and at higher altitudes, current inventory efforts are less than comprehensive. Acoustic sampling with bat detectors may help to overcome these limitations for insectivorous bats, but has yet to be tested in mainland SE Asia. To do so, we sampled bats while simultaneously recording the echolocation calls of insectivorous species commuting and foraging in a variety of karst habitats in north Vietnam. Monitoring of cave-dwelling bats was also undertaken. Discriminant function analysis of 367 echolocation calls produced by 30 insectivorous species showed that acoustic identification was feasible by correctly classifying 89. 1% of calls. In all habitats, acoustic sampling and capture methods recorded significantly more species each night than capture methods alone. Capture methods consequently failed to record 29% （ten spp. of aerial insectivores） of the bat fauna in commuting and foraging habitats and 11% （two spp. ） of that in our cave sample. Only four of these species were subsequently captured following significantly greater sampling effort. This strongly suggests that acoustic methods are indispensable for maximizing bat inventory completeness in SE Asia. As accurate inventories and monitoring are essential for effective species conservation, we recommend the inclusion of acoustic sampling in future studies of bat assemblages across the region [ Current Zoology 55 （5） ： 327 - 341, 2009].
基金supported by the China Natural Science Foundation (81290341 and 31621061 to ZLS)United States Agency for International Development Emerging Pandemic Threats PREDICT project (AID-OAA-A-14-00102)National Institute of Allergy and Infectious Diseases of the National Institutes of Health (Award Number R01AI110964)
文摘Previous studies indicated that fruit bats carry two betacoronaviruses,BatCoV HKU9 and BatCoV GCCDC1.To investigate the epidemiology and genetic diversity of these coronaviruses,we conducted a longitudinal surveillance in fruit bats in Yunnan province,China during 2009–2016.A total of 59(10.63%)bat samples were positive for the two betacorona-viruses,46(8.29%)for HKU9 and 13(2.34%)for GCCDC1,or closely related viruses.We identified a novel HKU9 strain,tentatively designated as BatCoV HKU9-2202,by sequencing the full-length genome.The BatCoV HKU9-2202 shared 83%nucleotide identity with other BatCoV HKU9 stains based on whole genome sequences.The most divergent region is in the spike protein,which only shares 68%amino acid identity with BatCoV HKU9.Quantitative PCR revealed that the intestine was the primary infection organ of BatCoV HKU9 and GCCDC1,but some HKU9 was also detected in the heart,kidney,and lung tissues of bats.This study highlights the importance of virus surveillance in natural reservoirs and emphasizes the need for preparedness against the potential spill-over of these viruses to local residents living near bat caves.
文摘We tested the prediction that at coarse spatial scales, variables associated with climate, energy, and productivity hy- potheses should be better predictor（s） of bat species richness than those associated with environmental heterogeneity. Distribution ranges of 64 bat species were estimated with niche-based models informed by 3629 verified museum specimens. The influence of environmental correlates on bat richness was assessed using ordinary least squares regression （OLS）, simultaneous autoregressive models （SAR）, conditional autoregressive models （CAR）, spatial eigenvector-based filtering models （SEVM）, and Classification and Regression Trees （CART）. To test the assumption of stationarity, Geographically Weighted Regression （GWR） was used. Bat species richness was highest in the eastern parts of southern Africa, particularly in central Zimbabwe and along the western border of Mozambique. We found support for the predictions of both the habitat heterogeneity and climate/productivity/energy hypothe- ses, and as we expected, support varied among bat families and model selection. Richness patterns and predictors of Miniopteridae and Pteropodidae clearly differed from those of other bat families. Altitude range was the only independent variable that was sig- nificant in all models and it was most often the best predictor of bat richness. Standard coefficients of SAR and CAR models were similar to those of OLS models, while those of SEVM models differed. Although GWR indicated that the assumption of stationa- rity was violated, the CART analysis corroborated the findings of the curve-fitting models. Our results identify where additional data on current species ranges, and future conservation action and ecological work are needed.
