The large larch beetle,Ips cembrae,is a significant pest causing the death of larch.In 2020,the attack density of I.cembrae on larch trap trees and standing trees was evaluated using sample sections placed along the t...The large larch beetle,Ips cembrae,is a significant pest causing the death of larch.In 2020,the attack density of I.cembrae on larch trap trees and standing trees was evaluated using sample sections placed along the trunk.As a defensive measure against I.cembrae,trap trees were highly effective in both spring and summer.The attack density increased with increasing trap tree surface area/volume.Galleries were established evenly throughout the entire trunk including the thin upper portion.When the number of trap trees was low and their capacity full,a continual aggregation of adults occurred due to pheromone communication,leading to attacks on healthy standing trees in the immediate vicinity.It was found that I.cembrae attacked standing trees from the trunk base,with a continual colonization of the stem up to 70%of the tree height in a time-differentiated progression of development stages.The attack density of I.cembrae on standing trees was up to 40%lower than on the trap trees.展开更多
Controls, especially effficiency controls on dynamical processes, have become major challenges in many complex systems. We study an important dynamical process, random walk, due to its wide range of applications for m...Controls, especially effficiency controls on dynamical processes, have become major challenges in many complex systems. We study an important dynamical process, random walk, due to its wide range of applications for modeling the transporting or searching process. For lack of control methods for random walks in various structures, a control technique is presented for a class of weighted treelike scale-free networks with a deep trap at a hub node. The weighted networks are obtained from original models by introducing a weight parameter. We compute analytically the mean first passage time （MFPT） as an indicator for quantitatively measurinM the et^ciency of the random walk process. The results show that the MFPT increases exponentially with the network size, and the exponent varies with the weight parameter. The MFPT, therefore, can be controlled by the weight parameter to behave superlinearly, linearly, or sublinearly with the system size. This work provides further useful insights into controllinM eftlciency in scale-free complex networks.展开更多
基金supported by Ministry of Agriculture of the Czech Republic in grant[QK1920433].“Influence of protective measuresagainst the populations of bark beetles according to population density”。
文摘The large larch beetle,Ips cembrae,is a significant pest causing the death of larch.In 2020,the attack density of I.cembrae on larch trap trees and standing trees was evaluated using sample sections placed along the trunk.As a defensive measure against I.cembrae,trap trees were highly effective in both spring and summer.The attack density increased with increasing trap tree surface area/volume.Galleries were established evenly throughout the entire trunk including the thin upper portion.When the number of trap trees was low and their capacity full,a continual aggregation of adults occurred due to pheromone communication,leading to attacks on healthy standing trees in the immediate vicinity.It was found that I.cembrae attacked standing trees from the trunk base,with a continual colonization of the stem up to 70%of the tree height in a time-differentiated progression of development stages.The attack density of I.cembrae on standing trees was up to 40%lower than on the trap trees.
基金Supported by the National Natural Science Foundation of China under Grant Nos 61173118,61373036 and 61272254
文摘Controls, especially effficiency controls on dynamical processes, have become major challenges in many complex systems. We study an important dynamical process, random walk, due to its wide range of applications for modeling the transporting or searching process. For lack of control methods for random walks in various structures, a control technique is presented for a class of weighted treelike scale-free networks with a deep trap at a hub node. The weighted networks are obtained from original models by introducing a weight parameter. We compute analytically the mean first passage time （MFPT） as an indicator for quantitatively measurinM the et^ciency of the random walk process. The results show that the MFPT increases exponentially with the network size, and the exponent varies with the weight parameter. The MFPT, therefore, can be controlled by the weight parameter to behave superlinearly, linearly, or sublinearly with the system size. This work provides further useful insights into controllinM eftlciency in scale-free complex networks.
