Species introduced to habitats outside their native range often escape control by their natural enemies.Besides competing with native species,an alien species might also affect the native herbivores by introducing a n...Species introduced to habitats outside their native range often escape control by their natural enemies.Besides competing with native species,an alien species might also affect the native herbivores by introducing a new source of different quality food.Here,we describe the case of northern red oak(Quercus rubra)invasion in Europe.We collected data on insect(moth Cydia spp.and weevil Curculio spp.)seed predation of northern red oak in its native(USA,North America)and invasive(Poland,Europe)range,as well as for sessile oaks(Quercus petrea)in Europe.We also evaluated the quality of acorns as hosts for weevil larvae by collecting infested acorns and measuring weevil developmental success,and quantifying acorn traits such as seed mass,tannins,lipids and protein concentration.We used DNA barcoding to identify insects to the species level.The predation by moths was similar and very low in both species and in both ranges.However,red oaks escape pre-dispersal seed predation by weevils in Europe.Weevil infestation rates of northern red oak acorns in their invasive range were 10 times lower than that of sessile oaks,and also 10 times lower than that of red oaks in North America.Furthermore,even when weevils oviposited into northern red oaks,the larvae failed to develop,suggesting that the exotic host created a trap for the insect.This phenomenon might gradually decrease the local abundance of the seed predator,and further aid the invasion.展开更多
Smart precision agriculture utilizes modern information and wireless communication technologies to achieve challenging agricultural processes.Therefore,Internet of Things(IoT)technology can be applied to monitor and d...Smart precision agriculture utilizes modern information and wireless communication technologies to achieve challenging agricultural processes.Therefore,Internet of Things(IoT)technology can be applied to monitor and detect harmful insect pests such as red palm weevils(RPWs)in the farms of date palm trees.In this paper,we propose a new IoT-based framework for early sound detection of RPWs using fine-tuned transfer learning classifier,namely InceptionResNet-V2.The sound sensors,namely TreeVibes devices are carefully mounted on each palm trunk to setup wireless sensor networks in the farm.Palm trees are labeled based on the sensor node number to identify the infested cases.Then,the acquired audio signals are sent to a cloud server for further on-line analysis by our fine-tuned deep transfer learning model,i.e.,InceptionResNet-V2.The proposed infestation classifier has been successfully validated on the public TreeVibes database.It includes total short recordings of 1754 samples,such that the clean and infested signals are 1754 and 731 samples,respectively.Compared to other deep learning models in the literature,our proposed InceptionResNet-V2 classifier achieved the best performance on the public database of TreeVibes audio recordings.The resulted classification accuracy score was 97.18%.Using 10-fold cross validation,the fine-tuned InceptionResNet-V2 achieved the best average accuracy score and standard deviation of 94.53%and±1.69,respectively.Applying the proposed intelligent IoT-aided detection system of RPWs in date palm farms is the main prospect of this research work.展开更多
Manglietia ventii is a highly endangered plant species endemic to Yunnan province in China, where there are only five known small populations. Despite abundant flowering there is very low fruit and seed set,and very f...Manglietia ventii is a highly endangered plant species endemic to Yunnan province in China, where there are only five known small populations. Despite abundant flowering there is very low fruit and seed set,and very few seedlings in natural populations, indicating problems with reproduction. The causes of low fecundity in M. ventii are not known, largely because of insufficient knowledge of the species pollination ecology and breeding system. We conducted observations and pollination experiments, and analyzed floral scents to understand the pollinatoreplant interactions and the role of floral scent in this relationship, as well as the species breeding system. Like the majority of Magnoliaceae, M. ventii has protogynous and nocturnal flowers that emit a strong fragrance over two consecutive evenings. There is a closing period(the pre-staminate stage) during the process of anthesis of a flower, and we characterize the key flowering process as an "open-close-reopen" flowering rhythm with five distinct floral stages observed throughout the floral period of this species: pre-pistillate, pistillate, pre-staminate, staminate,and post-staminate. Flowers are in the pistillate stage during the first night of anthesis and enter the staminate stage the next night. During anthesis, floral scent emission occurs in the pistillate and staminate stages. The effective pollinators were weevils(Sitophilus sp.) and beetles(Anomala sp.), while the role of Rove beetles(Aleochara sp.) and thrips(Thrips sp.) in pollination of M. ventii appears to be minor or absent. The major chemical compounds of the floral scents were Limonene, b-Pinene, a-Pinene, 1,8-Cineole, Methyl-2-methylbutyrate, p-Cymene, Methyl-3-methyl-2-butenoate and 2-Methoxy-2-methyl-3-buten, and the relative proportions of these compounds varied between the pistillate and staminate stages. Production of these chemicals coincided with flower visitation by weevils and beetles.The results of pollination experiments suggest that M. ventii is pollinator-dependent, and low seed s展开更多
基金This study was supported by the Polish National Science Foundation grant Preludium no.2015/17/N/NZ8/01565while MB was supported by Polish Foundation for Science scholarship‘Start’,and Etiuda NSF grant no.2015/16/T/NZ8/00018+1 种基金DNA sequencing was supported by PLAGANADO AGL2014-54739-R awarded to RBMAS recognizes the support of the U.S.National Science Foundation(DEB-1556707).
文摘Species introduced to habitats outside their native range often escape control by their natural enemies.Besides competing with native species,an alien species might also affect the native herbivores by introducing a new source of different quality food.Here,we describe the case of northern red oak(Quercus rubra)invasion in Europe.We collected data on insect(moth Cydia spp.and weevil Curculio spp.)seed predation of northern red oak in its native(USA,North America)and invasive(Poland,Europe)range,as well as for sessile oaks(Quercus petrea)in Europe.We also evaluated the quality of acorns as hosts for weevil larvae by collecting infested acorns and measuring weevil developmental success,and quantifying acorn traits such as seed mass,tannins,lipids and protein concentration.We used DNA barcoding to identify insects to the species level.The predation by moths was similar and very low in both species and in both ranges.However,red oaks escape pre-dispersal seed predation by weevils in Europe.Weevil infestation rates of northern red oak acorns in their invasive range were 10 times lower than that of sessile oaks,and also 10 times lower than that of red oaks in North America.Furthermore,even when weevils oviposited into northern red oaks,the larvae failed to develop,suggesting that the exotic host created a trap for the insect.This phenomenon might gradually decrease the local abundance of the seed predator,and further aid the invasion.
基金This research received the support from the Deputyship for Research&Innovation,Ministry of Education in Saudi Arabia through the project number(UB-26-1442).
文摘Smart precision agriculture utilizes modern information and wireless communication technologies to achieve challenging agricultural processes.Therefore,Internet of Things(IoT)technology can be applied to monitor and detect harmful insect pests such as red palm weevils(RPWs)in the farms of date palm trees.In this paper,we propose a new IoT-based framework for early sound detection of RPWs using fine-tuned transfer learning classifier,namely InceptionResNet-V2.The sound sensors,namely TreeVibes devices are carefully mounted on each palm trunk to setup wireless sensor networks in the farm.Palm trees are labeled based on the sensor node number to identify the infested cases.Then,the acquired audio signals are sent to a cloud server for further on-line analysis by our fine-tuned deep transfer learning model,i.e.,InceptionResNet-V2.The proposed infestation classifier has been successfully validated on the public TreeVibes database.It includes total short recordings of 1754 samples,such that the clean and infested signals are 1754 and 731 samples,respectively.Compared to other deep learning models in the literature,our proposed InceptionResNet-V2 classifier achieved the best performance on the public database of TreeVibes audio recordings.The resulted classification accuracy score was 97.18%.Using 10-fold cross validation,the fine-tuned InceptionResNet-V2 achieved the best average accuracy score and standard deviation of 94.53%and±1.69,respectively.Applying the proposed intelligent IoT-aided detection system of RPWs in date palm farms is the main prospect of this research work.
基金Funding(No.U1302262)to W.B.Sun from the NSFC-Yunnan joint fund on key projectsSurvey and Germplasm Conservation of PSESP in Southwest China(2017e2020,2017FY100100)+1 种基金partly supported by the Young Academic and Technical Leader Raising Foundation of Yunnan Province(2015HB091)the Science and Technology Research Program of Kunming Institute of Botany,the Chinese Academy of Science(KIB2016005)to G.Chen
文摘Manglietia ventii is a highly endangered plant species endemic to Yunnan province in China, where there are only five known small populations. Despite abundant flowering there is very low fruit and seed set,and very few seedlings in natural populations, indicating problems with reproduction. The causes of low fecundity in M. ventii are not known, largely because of insufficient knowledge of the species pollination ecology and breeding system. We conducted observations and pollination experiments, and analyzed floral scents to understand the pollinatoreplant interactions and the role of floral scent in this relationship, as well as the species breeding system. Like the majority of Magnoliaceae, M. ventii has protogynous and nocturnal flowers that emit a strong fragrance over two consecutive evenings. There is a closing period(the pre-staminate stage) during the process of anthesis of a flower, and we characterize the key flowering process as an "open-close-reopen" flowering rhythm with five distinct floral stages observed throughout the floral period of this species: pre-pistillate, pistillate, pre-staminate, staminate,and post-staminate. Flowers are in the pistillate stage during the first night of anthesis and enter the staminate stage the next night. During anthesis, floral scent emission occurs in the pistillate and staminate stages. The effective pollinators were weevils(Sitophilus sp.) and beetles(Anomala sp.), while the role of Rove beetles(Aleochara sp.) and thrips(Thrips sp.) in pollination of M. ventii appears to be minor or absent. The major chemical compounds of the floral scents were Limonene, b-Pinene, a-Pinene, 1,8-Cineole, Methyl-2-methylbutyrate, p-Cymene, Methyl-3-methyl-2-butenoate and 2-Methoxy-2-methyl-3-buten, and the relative proportions of these compounds varied between the pistillate and staminate stages. Production of these chemicals coincided with flower visitation by weevils and beetles.The results of pollination experiments suggest that M. ventii is pollinator-dependent, and low seed s
