Zhu Zhen-Qin, Zi Shu-Mei, Gao Li-Fang, Zhang Xiao-Dan, Liu Fang-Yuan, Wang Qian, Du Bo
School of Life Sciences, Lanzhou University, Lanzhou City, Gansu Province 730000, China.
College of Ecology, Lanzhou University, Lanzhou City, Gansu Province 730000, China.
Curr Zool. 2022 Aug 17;69(4):385-392. doi: 10.1093/cz/zoac064. eCollection 2023 Aug.
Altricial birds often display biased preferences in providing parental care for their dependent offspring, especially during food shortages. During this process, such inflexible rules may result in provisioning errors. To demonstrate how parents optimize their provisioning strategies, we proposed a "diagnosis model" of parental care to posit that parents will undergo a diagnosis procedure to test whether selecting against some particular offspring based on phenotype is an optimal strategy. We tested this model in an asynchronous hatching bird, the Azure-winged Magpie , based on 10 years of data about demography and parental provisioning behaviors. Given their higher daily survival rates, core offspring (those hatched on the first day) merits an investment priority compared with their marginal brood mates (those hatched on later days). However, a marginal offspring also merited a priority if it displayed greater weight gain than the expected value at the early post-hatching days. Parents could detect such a marginal offspring via a diagnosis strategy, in which they provisioned the brood at the diagnosis stage by delivering food to every nestling that begged, then biased food toward high-value nestlings at the subsequent decision stage by making a negative response to the begging of low-value nestlings. In this provisioning strategy, the growth performance of a nestling became a more reliable indicator of its investment value than its hatching order or competitive ability. Our findings provide evidence for this "diagnosis model of parental care" wherein parents use a diagnosis method to optimize their provisioning strategy in brood reduction.
晚成鸟在为其依赖的后代提供亲代抚育时,往往表现出有偏向的偏好,尤其是在食物短缺期间。在这个过程中,这种不灵活的规则可能会导致育雏失误。为了证明亲鸟如何优化它们的育雏策略,我们提出了一种亲代抚育的“诊断模型”,假定亲鸟会经历一个诊断过程,以测试基于表型对某些特定后代进行筛选是否是一种最优策略。我们基于10年的种群统计学和亲代育雏行为数据,在一种异步孵化的鸟类——灰喜鹊中对这个模型进行了测试。鉴于核心后代(第一天孵化出的雏鸟)具有更高的日存活率,与它们的边缘同胞(较晚孵化出的雏鸟)相比,理应优先得到投资。然而,如果一只边缘后代在孵化后的早期体重增加超过预期值,那么它也理应得到优先照顾。亲鸟可以通过一种诊断策略来识别这样的边缘后代,即在诊断阶段,它们会给每只乞食的雏鸟喂食来照顾整个雏鸟群,然后在随后的决策阶段,通过对低价值雏鸟的乞食做出负面反应,将食物偏向高价值的雏鸟。在这种育雏策略中,雏鸟的生长表现比其孵化顺序或竞争能力更能可靠地表明其投资价值。我们的研究结果为这种“亲代抚育诊断模型”提供了证据,即亲鸟使用一种诊断方法来优化它们在减少育雏数量时的育雏策略。