On the basis of data presented in [21] , we estimated the length of the developmental stages (egg hatching, larval and pupal development) and of the gonotrophic cycle as a function of temperature. To estimate, for instance, the length of the egg hatching period we used the following procedure: let e T be the length of the egg hatching period for temperatures T [ T ? :f15 0 C,20 0 C,25 0 C,30 0 C,35 0 Cg, as reported in [21] . We assume that e T~lE (T; P)ze T where l E (T; P) is a parametric function of the temperature T (P indicate the set of parameters) in a suitable set of functions, comprising exponential and parabolic functions, and e T is a random sample of a 0 mean normal distribution with unknown variance s 2 . The square error Err between predicted and observed length of the egg hatching period is defined as Err~P T[T ? (e T {l E (T; P)) 2 . ParametersP P were estimated by minimizing Err. The variances s 2 was computed as the average of the estimated residuals of the model (i.e., the average of the quadratic differences of (e T {l E (T;P P)) 2 between the observed data and the best model fit l E (T;P P)). The uncertainty of the parameters was estimated by using a technique similar to that used in [33] . Specifically, we simulated 1000 different fe T g T [T ? , obtained by perturbing the best-fit l E (T;P P) by adding a simulated error sampled from a normal distributed N(0,s s 2 ) and we repeated the optimization procedure described above. Finally, the rate of eggs hatching is defined as d E (T; P)~1=l E (T; P). The same technique was used to estimate the length of larval and pupal development and the length of the gonotrophic cycle. Results are reported in Table 1 . Fig. 2b shows a comparison between observed and modeled data.