Pedigree accumulation analysis: Combining methods from community ecology and population genetics for breeding adult estimation
- Estimates of the number of successfully breeding adults (NS) in a population can predict levels of recruitment. However, assessments of NS 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.
- To estimate NS, 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 NS. We also evaluated NS 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).
- We found unbiased NS 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.
- 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 NS that can facilitate population assessments.
|Publication Subtype||Journal Article|
|Title||Pedigree accumulation analysis: Combining methods from community ecology and population genetics for breeding adult estimation|
|Series title||Methods in Ecology and Evolution|
|Publisher||John Wiley & Sons|
|Contributing office(s)||Great Lakes Science Center|
|Google Analytic Metrics||Metrics page|