1. Estimates of the number of successfully breeding adults (N_S) in a population can predict levels of recruitment. However, assessments of N_S are often difficult to obtain because encounters with adults are limited due to life-history characteristics, low abundance or other constraints associated with access to critical habitats. Alternatively, efforts to sample individuals at earlier ontogenetic stages can be more tractable, resulting in more comprehensive samples.
2. To estimate N_S, we describe, evaluate and apply two nonparametric species richness estimators to information associated with genetic pedigree reconstruction. Simulations compared bias and precision associated with Chao and Jackknife methods when estimating N_S. We also evaluated N_S estimation sensitivity to two sources of variation associated with species reproductive ecology (variance in reproductive success and sex ratio skew) and genetic pedigree assignment error. Finally, the application of our novel method was demonstrated in two different species and systems (Chinook Salmon in Oregon, USA and Lake Sturgeon in Michigan, USA).
3. We found unbiased N_S estimates were generated across a broad range of offspring sample sizes using the Chao method. Empirical results corroborated simulation-based expectations and highlighted applications where parents and offspring are sampled, and when only offspring are sampled.
4. When offspring sample sizes are adequate and pedigree reconstruction errors are low, the combination of established methods from community ecology and genetic pedigree reconstruction provides an accurate alternative method to estimate N_S that can facilitate population assessments.

中文翻译：

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谱系积累分析：结合群落生态学和种群遗传学的方法进行育种成虫估计

1. 成功繁殖的成年人（数量估计ñ_小号）的人口可以预测招聘水平。然而，评估ñ_小号往往很难获得，因为与成人遭遇被有限的，由于拥有访问权限的重要栖息地相关的生活史特征，低丰度或其他约束。或者，在早期个体发育阶段对个体进行采样的努力可能更容易处理，从而产生更全面的样本。
2. 为了估计N _S，我们描述、评估和应用两个非参数物种丰富度估计器到与遗传谱系重建相关的信息。在估计N _S时，模拟比较了与 Chao 和 Jackknife 方法相关的偏差和精度。我们还评估了N _S估计对与物种生殖生态学相关的两个变异来源（繁殖成功和性别比例偏差的差异）和遗传谱系分配错误的敏感性。最后，我们的新方法的应用在两个不同的物种和系统（美国俄勒冈州的奇努克鲑鱼和美国密歇根州的鲟鱼湖）中得到了证明。
3. 我们发现使用 Chao 方法在广泛的后代样本量中生成了无偏N _S估计。实证结果证实了基于模拟的期望，并突出了对父母和后代进行采样以及仅对后代进行采样的应用。
4. 当后代样本量充足且谱系重建误差较低时，社区生态学和遗传谱系重建的既定方法相结合，提供了一种准确的替代方法来估计N _S，可以促进种群评估。