Reproductive data of individual insects are extremely hard to collect under natural conditions, thus the study of research questions related to oviposition has not advanced. Patterns of oviposition are often inferred only indirectly, through monitoring of host infestation, whereas the influence of age structure and several other factors on oviposition remains unknown. Using a new approach, in this article, we live‐trapped wild Ceratitis capitata (Wiedemann) (Diptera: Tephritidae) females on the Greek island of Chios during two field seasons. For their remaining lifetime, these females were placed individually in small cages and their daily oviposition was monitored. Reproduction rates between cohorts from different collection dates were then compared. The results showed that in the different captive cohorts the average remaining lifetime and reproduction were highly variable within and between seasons. Multivariate regression analysis showed that the month of capture had a significant effect on captive life span, average daily reproduction, and patterns of egg laying. The effect of year was significant on reproduction, but not on captive life span. These differences between sampling periods probably reflect differences in the availability of hosts and other factors that vary during the season and affect age structure and reproduction. Using a non‐parametric generalized additive model, we found a statistically significant correlation between the captive life span and the average daily reproduction. These findings and the experimental approach have several important implications.

中文翻译：

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来自希腊活捕获雌性的 Ceratitis capitalta 繁殖潜力的季节性趋势

在自然条件下，个体昆虫的繁殖数据极难收集，因此与产卵有关的研究问题的研究尚未取得进展。产卵模式通常只能通过监测宿主感染来间接推断，而年龄结构和其他几个因素对产卵的影响仍然未知。在本文中，我们使用一种新方法，在两个田间季节期间，在希腊希俄斯岛上活捉了野生头蠖（Wiedemann）（双翅目：实蝇科）雌性。在它们剩余的一生中，这些雌性被单独放置在小笼子中，并监测它们的每日产卵情况。然后比较来自不同收集日期的队列之间的繁殖率。结果表明，在不同的圈养群体中，平均剩余寿命和繁殖在季节内和季节之间变化很大。多元回归分析表明，捕获月份对圈养寿命、平均每日繁殖和产卵模式有显着影响。年份对繁殖的影响显着，但对圈养寿命的影响不显着。采样期之间的这些差异可能反映了宿主可用性的差异以及季节期间变化并影响年龄结构和繁殖的其他因素。使用非参数广义加性模型，我们发现圈养寿命与平均每日繁殖之间存在统计学上的显着相关性。这些发现和实验方法有几个重要的意义。