تحلیل سری زمانی پویایی جمعیت پسیل گلابی، cacopsylla pyri (hemiptera: psyllidae)، با استفاده از مدل arima روی نه رقم مختلف گلابی pyrus communis

پسیل یک آفت کلیدی در مناطق مهم کشت گلابی pyrus communis  در ایران است. در این پژوهش، مدل‌های سری زمانی ارتباط بین منبع (نُه رقم گلابی)-مصرف‌کننده (مراحل مختلف رشدی پسیل گلابی) برای تحلیل پویایی جمعیت بررسی شدند. سری های زمانی جمعیت هر مرحله رشدی پسیل گلابی مجموعه‌ای از مشاهدات است که با نمونه برداری منظمِ متغیر جمعیت تخم، پوره و حشره کامل پسیل گلابی در دوره زمانی چهار ساله (1399- 1402) به‌دست آمده است. مدل میانگین متحرک خودهمبسته یکپارچه(arima)  در سری های زمانی برای پیش‌بینی آینده جمعیت هر یک از مراحل رشدی تخم، پوره و حشره کامل پسیل گلابی روی نُه رقم گلابی به‌کار برده شد. نتایج نشان داد که میانگین تفاوت بین تراکم جمعیت پیش بینی شده توسط مدل و مشاهده شده در سه مرحله رشدی، معادل 36.88 حشره-روز بود. میانگین درصد مطلق خطا برای هر سه مرحله رشدی به‌طور متوسط ماهانه معادل 2.37 حشره-روز بود. حداقل این شاخص، معادل 29.12 حشره-روز (0.7 ماهانه) در مرحله حشره کامل در رقم پوتوماک و حداکثر آن معادل 522.53 حشره-روز (10.9 ماهانه) در مرحله پوره در رقم نطنزی بود. مقادیر خودهمبستگی های باقی‌مانده و خودهمبستگی های جزئی در اکثر مراحل رشدی و ارقام مختلف به‌صورت مطلق از 0.5 کوچک‌تر بود. در منحنی تغییرات تراکم جمعیت همه مراحل رشدی پسیل گلابی، یک روند سینوسی اتفاق می‌افتاد. روند تغییرات در مشاهدات با پیش بینی مدل یکسان بود. میانگین قدرمطلق ضریب تقاطعی در حدود 0.3 تا 0.4 متغیر بوده که نشان‌دهنده قدرت تشخیص هر مرحله رشدی نسبت به مرحله رشدی بعد از آن بوده است. حداکثر قدرت تشخیص در ارقام مختلف مربوط به انتقال جمعیت از مرحله پوره به حشره کامل بود. انعطاف پذیری مدل ها در جمعیت پسیل گلابی و امکان خود کالیبره کردن آن‌ها، این رویکرد را به ابزاری ارزشمند برای نظارت بر جمعیت این حشره تبدیل می کند.

time series analysis of pear psylla population dynamics, cacopsylla pyri (hemiptera: psyllidae), using arima model on nine different pear pyrus communis l. cultivars

introductionpsylla is a key pest in important pear pyrus communis -growing areas in iran. detection of population fluctuations in ecological models can be traced with time series data. population dynamics is the result of changes in the population size that ascend from the random and independent contribution of births, deaths, and migrations of population individual members. population dynamics can be simulated by considering the role of each individual in a time unit as an independent and separate random variable. mathematical models of resource-consumer relationships can understand miscellaneous patterns of population dynamics, leading to a set of population behavioral patterns under the influence of food resources. this research was conducted on the population dynamics of eggs, nymphs, and adults of pear psylla cacopsylla pyri l. under feeding conditions from nine pear cultivars in field conditions. psylla is a key pest of pears and is distributed worldwide. in the climatic conditions of regions like iran, where spring and summer are dry and rainfall is less, the indirect damage of honeydew secretions is more than the damage from sucking plant sap. material and methodsthe time series of the population of each growth stage of pear psylla is a group of observations obtained by regular variable sampling of the eggs, nymphs, and adult psylla population in a period of four years (2020-2023). the integrated autocorrelated moving average (arima) model was used to forecast the future pear psylla population on nine pear cultivars. arima model suitability criteria and information criterion bayesian normalized (bic) were calculated. the plots of residual autocorrelations and partial autocorrelations that show the degree of correlation of the residuals of the model in the actual forecast were premeditated. a cross-correlation model was used to replicate the population model of each developmental stage against the population route of another developmental stage. results and discussionthe fitted models were significant at the 0.01% level for the populations of pear psylla on nine cultivars. the arima time series model showed good capacity in forecasting the population of egg, nymph and adult. differences among the fit indices of the model were observed in all three developmental stages. the mobility of the growth stage has been one of the most important reasons for these differences. because with the increase in mobility, the accuracy of sampling usually decreases and population sampling becomes more difficult. the type of host cultivat has also been effective in determining the predictive power of the model. the values of residual autocorrelations and partial autocorrelations in most growth stages and different pear cultivars were smaller than 0.5 in absolute terms, and this indicates that the remaining effective data was not included in the fitting of the time series model in the minimum amount. a sinusoidal trend occurs in the curve of pears psylla population density fluctuations. the trend of changes in observations was the same as predicted by the model. in some stages such as adult and in cultivars such as shah miveh where the population densities were higher than normal, the sinusoidal trend was not observed in the population forecast by the model. the relationship between the population of alternating developmental stages has been direct and increasing and inverse and decreasing at different periods of seasons. these changes were caused by the difference in the pear cultivars quality for pear psylla growth stages. the average absolute value of the cross-correlation varied between 0.3 and 0.4, which indicates the average detection power of each developmental stage compared to the subsequent developmental stage.