Coccinellid pupae use an array of defensive strategies against their natural enemies. This study aims to assess the efficiency of gregarious pupation as a defensive mechanism against intraguild predators and cannibals...Coccinellid pupae use an array of defensive strategies against their natural enemies. This study aims to assess the efficiency of gregarious pupation as a defensive mechanism against intraguild predators and cannibals in coccinellid. The study was designed specifically （i） to determine the natural occurrence of gregarious pupation in the field for different coccinellid species, and （ii） to evaluate the adaptive value of gregarious pupation as a defensive mechanism against 2 types of predators （i.e., cannibals and intraguild predators）. In the field, gregarious pupation consisted of a group of 2-5 pupae. The proportion of gregarious pupation observed varied according to species, the highest rate being observed with Harmonia axyridis Pallas （Coccinellidae; 14.17%）. Gregarious pupation had no impact on the probability that intraguild predators and cannibals locate pupae. Intraguild predation occurred more often in site with gregarious pupation, while cannibalism occurred as often in site with gregarious pupation as in site with isolated pupa. However, for a specific pupa, the mortality rate was higher for isolated pupae than for pupae located in a gregarious pupation site both in the presence of intraguild predators and in the presence of cannibals. The spatial location of pupae within the group had no impact on mortality rate. Since it reduces the risk of predation, it is proposed that gregarious pupation act as a defensive mechanism for 11. axyridis pupae.展开更多
The cumulative sum （CUSUM） algorithm is proposed to detect the selfish behavior of a node in a wireless ad hoc network. By tracing the statistics characteristic of the backoff time between successful transmissions, ...The cumulative sum （CUSUM） algorithm is proposed to detect the selfish behavior of a node in a wireless ad hoc network. By tracing the statistics characteristic of the backoff time between successful transmissions, a wireless node can distinguish if there is a selfish behavior in the wireless network. The detection efficiency is validated using a Qualnet simulator. An IEEE 802.11 wireless ad hoc network with 20 senders and 20 receivers spreading out randomly in a given area is evaluated. The well-behaved senders use minimum contention window size of 32 and maximum con- tention window size of I 024, and the selfish nodes are assumed not to use the binary exponential strategy for which the contention window sizes are both fixed as 16. The transmission radius of all nodes is 250 m. Two scenarios are investigated： a single-hop network with nodes spreading out in 100 m^100 m, and all the nodes are in the range of each other; and a multi-hop network with nodes spreading out in 1 000 m~ 1 000 m. The node can monitor the backoff time from all the other nodes and run the detection algorithms over those samples. It is noted that the threshold can significantly affect the detection time and the detection accuracy. For a given threshold of 0.3 s, the false alarm rates and the missed alarm rates are less than 5%. The detection delay is less than 1.0 s. The simulation results show that the algorithm has short detection time and high detection accuracy.展开更多
文摘Coccinellid pupae use an array of defensive strategies against their natural enemies. This study aims to assess the efficiency of gregarious pupation as a defensive mechanism against intraguild predators and cannibals in coccinellid. The study was designed specifically （i） to determine the natural occurrence of gregarious pupation in the field for different coccinellid species, and （ii） to evaluate the adaptive value of gregarious pupation as a defensive mechanism against 2 types of predators （i.e., cannibals and intraguild predators）. In the field, gregarious pupation consisted of a group of 2-5 pupae. The proportion of gregarious pupation observed varied according to species, the highest rate being observed with Harmonia axyridis Pallas （Coccinellidae; 14.17%）. Gregarious pupation had no impact on the probability that intraguild predators and cannibals locate pupae. Intraguild predation occurred more often in site with gregarious pupation, while cannibalism occurred as often in site with gregarious pupation as in site with isolated pupa. However, for a specific pupa, the mortality rate was higher for isolated pupae than for pupae located in a gregarious pupation site both in the presence of intraguild predators and in the presence of cannibals. The spatial location of pupae within the group had no impact on mortality rate. Since it reduces the risk of predation, it is proposed that gregarious pupation act as a defensive mechanism for 11. axyridis pupae.
基金Supported by National Natural Science Foundation of China (No. 60702038)National High Technology Research and Development Program of China ("863"Program, No. 2007AA01Z220)Cultivation Fund of Innovation Project,Ministry of Education of China (No. 708024)
文摘The cumulative sum （CUSUM） algorithm is proposed to detect the selfish behavior of a node in a wireless ad hoc network. By tracing the statistics characteristic of the backoff time between successful transmissions, a wireless node can distinguish if there is a selfish behavior in the wireless network. The detection efficiency is validated using a Qualnet simulator. An IEEE 802.11 wireless ad hoc network with 20 senders and 20 receivers spreading out randomly in a given area is evaluated. The well-behaved senders use minimum contention window size of 32 and maximum con- tention window size of I 024, and the selfish nodes are assumed not to use the binary exponential strategy for which the contention window sizes are both fixed as 16. The transmission radius of all nodes is 250 m. Two scenarios are investigated： a single-hop network with nodes spreading out in 100 m^100 m, and all the nodes are in the range of each other; and a multi-hop network with nodes spreading out in 1 000 m~ 1 000 m. The node can monitor the backoff time from all the other nodes and run the detection algorithms over those samples. It is noted that the threshold can significantly affect the detection time and the detection accuracy. For a given threshold of 0.3 s, the false alarm rates and the missed alarm rates are less than 5%. The detection delay is less than 1.0 s. The simulation results show that the algorithm has short detection time and high detection accuracy.
