# Spatial Dynamics of Olive Fruit Fly Adults in the Framework of a Monitoring Trap Network
## 4 Discussion
So, the records of the baited traps may not provide an estimation of the population changes in the field during the period where there is no fruit damage, but they provide a good estimation of the field population changes in the period where there is increased damage. This is also observable from the great difference in the September peak in Spain (first phase, almost no damage) and the high similarity in October, likely due to a generation completion (established phase). In a previous work, [PERSON] et al. [15], comparing captures in McPhail traps with flies sampled from a canopy of olive trees, reported that catches in traps were correlated with flies dropped from the tree canopy in July-August, but no relationship was found in September, when a significant drop of the population levels was recorded. Damage levels could be influenced also by the olive cultivar's susceptibility to _B. olea_[28]. In our case, the cultivar groups in different countries were different and can represent an additional source of variability that we did not consider. Therefore, we must consider our comparisons across different sites with caution because the different cultivar's susceptibilities could influence the proposed dynamics from a quantitative point of view, particularly the number of adults that enter the grove to actively look for food and the amount of fruit damage. In general, catches in traps can be influenced by factors dependent on the type of attractant device used or on environmental factors such as humidity and temperature, which affect the evaporation of attractants. Furthermore, only some of the individuals respond to the attractive stimuli, depending on the physiological stage of the individual and the phenological phase of the plant. For example, McPhail traps baited with protein hydrolysate lures tend to overestimate early season olive fruit fly populations and the proportion of gravid females present [14]. In our experiments, it was also observed that BTs clearly overestimate pest numbers in the field not only in the early season but also in periods without an established population. Therefore, trap catches in these periods should be considered with caution in decision-making processes. It was reported that male flies are not very attracted to traps baited with pheromones during spring and early summer, when olives are not hostable [29]. However, at the time we ran the experiments, mainly in summer and autumn, male and female distributions were almost always spatially associated, except in situations of very low catches with random spatial patterns and when the male and female temporal dynamics were very similar within the same category of trap. In the Tunisia case, when the survey was anticipated to take place in June-July, males responded much better to BTs than UTs, suggesting that the type of device and attractant used are not exposed to seasonal variations in attractiveness. Although monitoring with traps is considered fundamental and can provide useful indications, it is affected by various limitations that suggest that the data collected in the field should always be evaluated with caution. Furthermore, while traps offer valuable insights into population presence, establishing a direct correlation between trap catches and pest population levels in olive groves remains challenging. According to our results, this correlation was found to be significant only when fruit damage occurred, whereas BTcatches overestimate the population levels in the other cases. This result indicates that the interpretation of the trap data may be less valuable in summer or other periods without established populations. Therefore, economic thresholds that combine adult captures with estimates of active infestation may yield better results than taking either aspect individually. Taking this into account in the efforts to obtain more accurate predictions of both the field population level and the severity of damage would enhance the reliability of damage forecasts and support timely decision-making [13].