Genetic architecture facilitates then constrains adaptation in a host-parasite coevolutionary arms race.

In coevolutionary arms races, interacting species impose selection on each other, generating reciprocal adaptations and counter adaptations. This process is typically enhanced by genetic recombination and heterozygosity, but these sources of evolutionary novelty may be secondarily lost when uniparental inheritance evolves to ensure the integrity of sex-linked adaptations. We demonstrate that host-specific egg mimicry in the African cuckoo finch Anomalospiza imberbis is maternally inherited, confirming the validity of an almost century-old hypothesis. We further show that maternal inheritance not only underpins the mimicry of different host species but also additional mimetic diversification that approximates the range of polymorphic egg "signatures" that have evolved within host species as an escalated defense against parasitism. Thus, maternal inheritance has enabled the evolution and maintenance of nested levels of mimetic specialization in a single parasitic species. However, maternal inheritance and the lack of sexual recombination likely disadvantage cuckoo finches by stifling further adaptation in the ongoing arms races with their individual hosts, which we show have retained biparental inheritance of egg phenotypes. The inability to generate novel genetic combinations likely prevents cuckoo finches from mimicking certain host phenotypes that are currently favored by selection (e.g., the olive-green colored eggs laid by some tawny-flanked prinia, Prinia subflava, females). This illustrates an important cost of coding coevolved adaptations on the nonrecombining sex chromosome, which may impede further coevolutionary change by effectively reversing the advantages of sexual reproduction in antagonistic coevolution proposed by the Red Queen hypothesis.

Rigorous meta-analysis of life history correlations by simultaneously analyzing multiple population dynamics models.

Correlations among life history parameters have been discussed in the ecological literature for over 50 years, but are often estimated while treating model estimates of demographic rates such as natural mortality (M) or individual growth (k) as "data." This approach fails to propagate uncertainty appropriately because it ignores correlations in estimation errors between parameters within a species and differences in estimation error among species. An improved alternative is multi-species mixed-effects modeling, which we approximate using multivariate likelihood profiles in an approach that synthesizes information from several population dynamics models. Simulation modeling demonstrates that this approach has minimal bias, and that precision improves with increased number of species. As a case study, we demonstrate this approach by estimating M/k for 11 groundfish species off the U.S. West Coast using the data and functional forms on which pre-existing, peer-reviewed, population dynamics models are based. M/k is estimated to be 1.26 for Pacific rockfishes (Sebastes spp.), with a coefficient of variation of 76% for M given k. This represents the first-ever estimate of correlations among life history parameters for marine fishes using several age-structured population dynamics models, and it serves as a standard for future life history correlation studies. This approach can be modified to provide robust estimates of other life history parameters and correlations, and requires few changes to existing population dynamics models and software input files for both marine and terrestrial species. Specific results for Pacific rockfishes can be used as a Bayesian prior for estimating natural mortality in future fisheries management efforts. We therefore recommend that fish population dynamics models be compiled in a global database that can be used to simultaneously analyze observation-level data for many species in life history meta-analyses.