Browsing by Author "Shi, Pei-Jian"

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Can a Semiochemical-Based Trapping Method Diminish Damage Levels Caused by Rhabdoscelus obscurus (Coleoptera: Curculionidae)?
(2012-09) Reddy, Gadi V. P.; Shi, Pei-Jian; Mann, C. R.; Mantanona, D. M. H.; Dong, Z.
The New Guinea sugarcane weevil, Rhabdoscelus obscurus (Boisduval) (Coleoptera: Curculionidae), is an important pest of palms, ornamental nurseries, and sugarcane in the Pacific Islands. Without effective control methods, R. obscurus populations can cause major or complete loss of palm production in Guam and other Micronesian Islands. Moreover, R. obscurus has inflicted severe attacks on coconut trees on Guam. The role of monitoring is important in judging the dynamics of R. obscurus and recording area wide population trends. There is no precise research information available on the trap catch threshold levels relative to the damage caused by R. obscurus. Here we investigated the assessment of trap catch threshold levels and the potential for predicting R. obscurus larval damage by using adult pheromone trap captures. Spatial patterns of capture were studied in relation to subsequent larval damaged betel nut plants at various locations in Guam, United States, during 2010-2012. The generalized additive model was used to describe the effects of the treatment level (traps/ha), ranging from 0 to 12, and time on reducing the damage of R. obscurus to palms. We find that these two predictors are statistically significant, and the treatment level is demonstrated to be the crucial predictor for reducing the damage. There is no significant difference in effectively controlling the damage between the treatment levels of 9 and 12 traps/ha. At least 9 traps/ha is suggested for effectively controlling the damage based on results from the current study.
Comparison of Thermal Performance Equations in Describing Temperature-Dependent Developmental Rates of Insects: (I) Empirical Models
(2015-12) Shi, Pei-Jian; Reddy, Gadi V. P.; Chen, Lei; Ge, Feng
Temperature greatly affects the developmental duration of insects at their different stages, and many mathematical models exist for describing their temperature-dependent developmental rates. It is important to choose a suitable model to predict outbreaks of pest insects under climate change. However, previous comparisons among these models were usually based on a single species. In the present study, we compared the six nonlinear models (the BriÃ©re-1, BriÃ©re-2, Lactin, Performance-2, beta, and Ratkowsky models) based on the goodness of fit and the trade-off between the modelâ€™s goodness of fit and structural complexity, using 10 temperature-dependent developmental rate datasets on insects to make the conclusions general. We found that the square root model (i.e., the Ratkowsky model) fitted all datasets well, and the curve shape produced by this model also approximates the curve shape of thermodynamically based mathematical models. The square root model was originally derived to be applicable to the growth rates of bacteria, and until now it has been generally ignored in entomology. We were mainly concerned with the predicted results obtained by using this model on observations of temperature-dependent developmental rates. We found that the square root model described well the pooled developmental rates in the low-, mid-, and high-temperature ranges, and we believe that it merits wider use in entomology.
Comparison of Thermal Performance Equations in Describing Temperature-Dependent Developmental Rates of Insects: (III) Phenological Applications
(2018-11) Shi, Pei-Jian; Fan, Mei-Ling; Reddy, Gadi V. P.
The developmental times of poikilotherms at different stages are significantly affected by temperature. Most mathematical models describing the temperature-dependent developmental rates of poikilotherms are built according to the experimental data at various constant temperatures. However, these models can also be applied to the developmental rates at variable temperatures. It is more meaningful to use models to predict the occurrence times of pest insects that actually represent the completion for a particular developmental stage (e.g., hatching, pupation, eclosion) under a natural thermal environment. For some developmental stages, insects might experience a period of high temperatures. In this case, skewed bell-shaped nonlinear models are more reasonable than the linear and exponential models because in the high-temperature region the developmental rate decreases with temperature increasing. We used the accumulated developmental progress method that combines three representative nonlinear models to compare the model validity in predicting the egg\'s earliest hatching date of bamboo locust in different years. We found that for the springtime phenological event the simple Arrhenius\' equation obtains the best goodness of fit. This study also provides a general R function that permits users to employ nonlinear parametric models to predict the occurrence times of insect phenology. In fact, if the investigation data cannot reflect the temperature-based phenological models proposed here, we have to consider whether the data set is reliable or whether the temperature is the crucial factor that determines the occurrence time of interest. The present study is valuable for the integrated management of pest insects because the biological or chemical control timing relies on the prediction on the occurrence time of phenological events.
Dispersal distance determines the exponent of the spatial Taylor's power law
(2016-09) Shi, Pei-Jian; Sandhu, Hardev S.; Reddy, Gadi V. P.
The equation describing a power-law relationship between the mean and variance of population abundance in space or time is known as Taylor's power law (TPL), initially observed in samples of insects. Factors determining the TPL exponent are of particular concern to ecologists because the observations of the exponent usually range 1-2. Recent studies have suggested that TPL is caused solely by statistical artifacts rather than biological processes, with the corresponding statistical models lacking linkages to explicit population demography. In this study, we used two special forms of the Neyman-Scott cluster point process to study the effect of offspring dispersal distance from the parents on the TPL exponent. Results showed that dispersal distance could largely affect the TPL exponent. The response curve of TPL exponent to dispersal distance is similar to the shape of the left-skewed gamma distribution function multiplied by a constant which can permit its maximum value to exceed 1. That means, short-distance dispersals could produce large TPL exponents relative to the whole response curve. However, the TPL exponent will decline in the case that the dispersal is extremely short or long. To better understand the function of the exponent of TPL on fitness, we attempted to link plant seed dispersal ability to the TPL exponent, and we discussed the trade-off between investing in propagation energy and in performance energy of plants. Dispersal overlap of offspring each other to an extent can cause a large TPL exponent, providing maximum fitness in a population. A novel theoretical frame was proposed to explain the role of spatial TPL relationships in affecting the fitness of plants.
Nonparametric Estimation of Interspecific Spatio-Temporal Niche Separation Between Two Lady Beetles (Coleoptera: Coccinellidae) in Bt Cotton Fields
(2015-07) Lu, Zeng-Bin; Shi, Pei-Jian; Reddy, Gadi V. P.; Li, Lin-Mao; Men, Xing-Yuan; Ge, Feng
Predaceous lady beetles are important natural enemies of many insect pests in agro-ecosystem. The altered agricultural practices associated with widespread adoption of Bt cotton may have potential effects on the spatio-temporal patterns of predaceous lady beetles, as the composition and abundance of nontarget sucking pests have been changed in Bt cotton fields. In the current study, the spatio-temporal patterns of two important lady beetles, Harmonia axyridis (Pallas) (Coleoptera: Coccinellidae) and Propylea japonica (Thunberg) (Coleoptera: Coccinellidae), were surveyed in Bt cotton fields. A nonparametric method associated with Monte Carlo tests was used to address and test whether niche segregation occurred between H. axyridis and P. japonica. The results showed that the dominant region occupied by P. japonica was toward northeast across the season, whereas H. axyridis had higher presence to the southwest. The temporal patterns of H. axyridis and P. japonica also differed significantly, and the highest levels of each species occurred in different locations from each other on each sampling date in the same Bt cotton fields. In total, there were strong spatio-temporal separation patterns between these two species in Bt cotton fields. These spatio-temporal patterns may produce complementary impacts on prey, and this in turn could be used to strengthen the biological control of insect pests by these two lady beetles.
The seesaw effect of winter temperature change on the recruitment of cotton bollworms Helicoverpa armigera through mismatched phenology
(2015-12) Reddy, Gadi V. P.; Shi, Pei-Jian; Hui, Cang; Cheng, Xiaofei; Ouyang, Fang; Ge, Feng
Knowing how climate change affects the population dynamics of insect pests is critical for the future of integrated pest management. Rising winter temperatures from global warming can drive increases in outbreaks of some agricultural pests. In contrast, here we propose an alternative hypothesis that both extremely cold and warm winters can mismatch the timing between the eclosion of overwintering pests and the flowering of key host plants. As host plants normally need higher effective cumulative temperatures for flowering than insects need for eclosion, changes in flowering time will be less dramatic than changes in eclosion time, leading to a mismatch of phenology on either side of the optimal winter temperature. We term this the “seesaw effect.” Using a long-term dataset of the Old World cotton bollworm Helicoverpa armigera (Hübner) (Lepidoptera: Noctuidae) in northern China, we tested this seesaw hypothesis by running a generalized additive model for the effects of the third generation moth in the preceding year, the winter air temperature, the number of winter days below a critical temperature and cumulative precipitation during winter on the demography of the overwintering moth. Results confirmed the existence of the seesaw effect of winter temperature change on overwintering populations. Pest management should therefore consider the indirect effect of changing crop phenology (whether due to greenhouse cultivation or to climate change) on pest outbreaks. As arthropods from mid- and high latitudes are actually living in a cooler thermal environment than their physiological optimum in contrast to species from lower latitudes, the effects of rising winter temperatures on the population dynamics of arthropods in the different latitudinal zones should be considered separately. The seesaw effect makes it more difficult to predict the average long-term population dynamics of insect pests at high latitudes due to the potential sharp changes in annual growth rates from fluctuating minimum winter temperatures.
Timing of cherry tree blooming: Contrasting effects of rising winter low temperatures and early spring temperatures
(2017-06) Shi, Pei-Jian; Chen, Zhenghong; Reddy, Gadi V. P.; Hui, Cang; Huang, Jianguo; Xiao, Mei
Phenology reflects the interplay of climate and biological development. Early spring phenological phenomena are particularly important because the end of diapause or dormancy is related not only to heat accumulation in the early spring but also probably to winter low temperatures. Although a warmer winter can reduce overwintering mortality in many insects and plants, it also reduces the accumulation of chilling time that often triggers the end of diapause or dormancy. We examined a continuous 67-year time series of the first flowering date of cherry trees and compared three phenological models based on the temperature-dependent developmental rate: (i) the accumulated degree days (ADD) method, (ii) the number of days transferred to a standardized temperature (DTS) method, and (iii) the accumulated developmental progress (ADP) method. The ADP method performed the best but only slightly better than the DTS method. We further explained the residuals from the ADP method by an additive model using the mean winter minimum daily temperatures, the number of days with low temperatures (represented by daily minimum temperature) below a critical low temperature, and the minimum annual extreme temperature. These three temperature variables explained more than 57.5% deviance of the ADP model residuals. Increased mean winter low temperatures can delay the blooming of cherry trees by reducing the accumulation of chilling time, whereas reduced numbers of cold days can shift the blooming to become earlier. Overall, rising winter low temperatures will delay the flowering time, while rising early spring temperatures directly shift earlier the flowering time. The flowering time has been shifted to earlier, and the balance from the opposing effects of rising winter low temperatures and early spring temperatures explains this shift.