A Method of Describing and Using Variability in Development Rates for the Simulation of Insect Phenology

Abstract

An analytical method for the description of intrinsic variability in insect development rates for incorporation in phenology models is presented. Two sets of experimental data are used as examples. The method is easy to apply, can describe data accurately, produces highly realistic simulations of insect development, and is amenable to the simulation of age-dependent mortality, feeding, and reproduction. The method was developed for univoltine insects with discrete generations, but it can also be applied to multivoltine species with overlapping generations. A modification of the method to handle small samples is also discussed and applied to data.

Development Time Variability: Adaptation of Régnière’s Method to the Intrinsic Variability of Belgian Lucilia Sericata (Diptera, Calliphoridae) Population

“…To include this intrinsic variability in development-time duration estimation, Régnière [18] describes a method based on a correction factor handset to median developmental value. Interestingly, median is an often used synthetic value and is recommended by Richards and Villet [14] in the context of forensic entomology.…”

Degree-Day Prediction Models for the Flight Phenology of Western Bean Cutworm (Lepidoptera: Noctuidae) Assessed with the Concordance Correlation Coefficient

“…To determine how well the selected calculation method, start date, and lower and upper thresholds derived from D 25% could predict entire annual flight distributions, values for cumulative moth capture were converted to percentages of annual totals at each development site-year, and then regressed against accumulated degree-days, as calculated with the chosen model (e.g., Régnière 1984, Broatch et al 2006, Nam and Choi 2014. The pattern in cumulative flight was then analyzed using three alternative probability distribution functions.…”

“…Second was a log-logistic function, substituting ln(D) for D into equation [3]. The third function was a Weibull distribution, 1981-1982, 1984-1985, 1987-1988, 2004, 1986, 2000-2003, 2005Clay Center 1994-1997, 2001, 2003-20041999, 2002, 2005-2007Concord 1984, 1990, 1993, 1995-1997, 2000-2002, 2005, 20071981, 1991-1992, 1994-1999, 2003-2004, 2006North Platte 1989-1990, 1993-1995, 2001-2003, 20061986-1988, 1991-1992, 1996-1997, 1999, 2005, 2007 Clay Center ...…”

Phenology, population ecology, and rarity of the New Zealand ribbonwood aphid,Paradoxaphis plagianthi

“…2A), and suggested that development from birth to first reproduction requires a total of q = 212° days above a threshold temperature of b = 5.0°C. The variability in maturation time V was modelled best by the two-parameter Régnière (Régnière 1984) with steepness a = 31.2 and skew b = 3.21 (Fig. 2B).…”

“…The variability in development rate was modelled using Wiebull (Wagner et al 1984), logistic (Dennis et al 1986), and Régnière (Régnière 1984) functions as described by Wagner et al (1984). The best models were selected using Akaike's Information Criterion (Akaike 1973).…”