Jukka Jokela

Metals and per- and polyfluoroalkyl substances (PFAS) represent a significant environmental concern, yet their association with epigenetic age acceleration (EAA) remain largely understudied in marine mammals. Here, associations between EAA in common dolphins ( Delphinus delphis ) and life history (sex and sexual maturity), trace metals, and PFAS were investigated. EAA was calculated as the residual in the regression of epigenetic age vs chronological age, hence providing a direct measure of the deviation of the epigenetic age of an organism (positive or negative) by comparison with expectation, given their actual chronological age. Sixteen trace elements were quantified in hepatic and renal tissues (n = 53). In addition, 28 PFAS were quantified in hepatic tissue (n = 58). Associations between EAA and explanatory variables were assessed using regression-based and multivariate modelling approaches (linear models and canonical analysis of principal coordinates). No effect of sex was observed, although sexual maturity did significantly increase EAA. Exposure to metals was significantly associated with variation in EAA, explaining 55.4% of the variation, with hepatic metals (Se, Zn, Cu, Al, Mn) driving this relationship. Although EAA was not significantly related to the total PFAS exposure overall, a subset of PFAS variables (PFBA, PFDA, PFHxS-B, PFNA) showed significant association with EAA after adjusting for sex and sexual maturity. Together, these subsets of metal and PFAS variables, in addition to the selenium-to-mercury (Se:Hg) molar ratio, explained 66.7% of the variation in EAA. Our results identify sexual maturity and specific contaminant mixtures as key potential drivers of EAA in common dolphins, highlighting the possible use of EAA as a biomarker of environmental and physiological stress in marine mammals.

Faster evolution of mitochondrial genomes relative to nuclear genomes creates selective pressure on nuclear genes involved in mitochondrial function to preserve mitonuclear compatibility required for energy production. In isolated populations, such coevolution occurs independently. Upon secondary contact, selection against mismatched mitonuclear combinations or for advantageous mitochondrial variants together with their co‐adapted nuclear backgrounds can generate asymmetric gene flow between genomes, resulting in mitonuclear discordance. Under these scenarios, nuclear‐encoded mitochondrial genes are expected to exhibit divergence concordant with the mitochondrial genome. Mitonuclear discordance has been reported in the trematode parasite Atriophallophorus winterbourni , endemic to New Zealand, and attributed to vicariant isolation followed by postglacial recolonization. Here, we used high‐coverage whole‐genome pooled resequencing of parasites from five lakes across three geographic regions to characterize genome‐wide patterns of divergence and test whether selection on mitonuclear interactions underlies this discordance. We identified three geographically structured mitochondrial haplotypes alongside low nuclear differentiation maintained by extensive but asymmetric gene flow. The central Canterbury population showed discordant mitochondrial and nuclear genome affinities. Most mutations distinguishing the two mitotype groups were synonymous (85%). Of nuclear‐encoded mitochondrial genes, only 48% were polymorphic; among these, 95% followed genome‐wide nuclear divergence patterns, while 5% showed mildly reduced divergence between closely related mitotypes. Instead, loci with divergence patterns concordant with mtDNA (0.09% of the genome) were enriched for functions unrelated to mitochondria and potentially related to host–parasite interactions, suggesting host‐driven adaptive nuclear introgression with mitochondrial co‐segregation. These results highlight the utility of genome‐wide data in disentangling the mechanisms underlying mitonuclear discordance.

Saccharomyces cerevisiae is occasionally infected by totiviruses and their toxin-encoding satellites. Totiviruses and their satellites coexist but with an asymmetric dependence on the totivirus for maintenance inside the host cell. Satellites provide their yeast hosts with inhibitory toxins and the necessary self-immunity; loss of the satellite equates to loss of immunity. Because mycoviruses lack known extracellular stages, and sex is considered rare, mycoviruses are assumed to be transmitted vertically, implying infection states should correlate with host genotypes. However, totivirus–satellite coinfections are rarely examined in natural populations, leaving their associations with host genotypes poorly understood. We screened a multiyear population of S. cerevisiae isolates from New Zealand to examine the stability of host-virus associations over time, both within and across genotypes. While 55% of wild isolates harbored infections, only 37% of these included toxin-encoding satellites. Genotypes that persisted across years typically maintained consistent infection states. However, we observed stepwise transitions including acquisitions of totiviruses and satellites. Genotypes clustered strongly by infection state, supporting vertical transmission while suggesting that outcrossing is not responsible for the mycovirus acquisitions. Despite infection changes, genotype clustering by infection state remained intact, suggesting transitions are transient and that host genotypes may have optimal totivirus-satellite infection states.

Host–parasite interactions are influenced by present and past eco‐evolutionary interactions and the local environment. An ecological community defines the potential host range of each parasite and the potential parasite diversity of each host species. Past and present processes translate potential to realised interaction niches of parasite and host species. Host–parasite interactions are antagonistic, which may slow the saturation of their interaction niches. Intervality, a property of bipartite networks, measures saturation of interaction niches. Intervality of a community increases as the interaction niches of species of one guild (e.g. hosts) become saturated for their interactions with another guild (e.g. parasites). Characteristics driving intervality in host and parasite communities are largely unknown, as well as the effect of environmental change on intervality of these communities. In our study, we assess if the characteristics ‘phylogenetic relatedness' and ‘overlap in ecological interactions' explain intervality of rodent host–helminth parasite communities. In addition, we contrast intervality of these communities from habitats that differ in their history of human‐driven modification. We performed the analyses for the interaction niches of both parasites and hosts, independently. Our results indicated that host and parasite communities were non‐interval or significantly less interval than expected by chance. Phylogenetic relatedness and overlap in ecological interactions did not explain the maximum values of intervality. We speculate that antagonistic coevolution in host–parasite communities may hinder communities to reach saturation, which would explain why it is difficult to find the characteristics that explain intervality of a community. Interestingly, intervality of the interaction niche of parasites (host range) increased with habitat modification (i.e. saturation increased), whereas intervality of the interaction niche of hosts (parasite diversity) decreased as habitat modification increased. These opposite trends suggest that interaction niches of parasites and hosts respond differently to habitat modification.

Ecological interactions influence evolutionary dynamics by selecting upon fitness variation within species. Antagonistic interactions often promote genetic and species diversity, despite the inherently suppressive effect they can have on the species experiencing them. A central aim of evolutionary ecology is to understand how diversity is maintained in systems experiencing antagonism. In this review, we address how certain single-celled and dimorphic fungi have evolved allelopathic killer phenotypes that engage in antagonistic interactions. We discuss the evolutionary pathways to the production of lethal toxins, the functions of killer phenotypes and the consequences of competition for toxin producers, their competitors and toxin-encoding endosymbionts. Killer phenotypes are powerful models because many appear to have evolved independently, enabling across-phylogeny comparisons of the origins, functions and consequences of allelopathic antagonism. Killer phenotypes can eliminate host competitors and influence evolutionary dynamics, yet the evolutionary ecology of killer phenotypes remains largely unknown. We discuss what is known and what remains to be ascertained about killer phenotype ecology and evolution, while bringing their model system properties to the reader's attention.

Bipartite network analysis is a powerful tool to study the processes structuring interactions in ecological communities. In applying the method, it is assumed that the sampled interactions provide an accurate representation of the actual community. However, acquiring a representative sample may be difficult as not all species are equally abundant or easily identifiable. Two potential sampling issues can compromise the conclusions of bipartite network analyses: failure to capture the full range of interactions (sampling completeness) and use of a taxonomic level higher than species to evaluate the network (taxonomic resolution). We asked how commonly used descriptors of bipartite antagonistic communities (modularity, nestedness, connectance, and specialization [H₂′]) are affected by reduced host sampling completeness, parasite taxonomic resolution, and their crossed effect, as they are likely to co‐occur. We used a quantitative niche model to generate weighted bipartite networks that resembled natural host–parasite communities. The descriptors were more sensitive to uncertainty in parasite taxonomic resolution than to host sampling completeness. When only 10% of parasite taxonomic resolution was retained, modularity and specialization decreased by ~76% and ~12%, respectively, and nestedness and connectance increased by ~114% and ~345% respectively. The loss of taxonomic resolution led to a wide range of possible communities, which made it difficult to predict its effects on a given network. With regards to host sampling completeness, standardized nestedness, connectance, and specialization were robust, whereas modularity was sensitive (~30% decrease). The combination of both sampling issues had an additive effect on modularity. In communities with low effort for both sampling issues (50%–10% of sampling completeness and taxonomic resolution), estimators of modularity, and nestedness could not be distinguished from those of random assemblages. Thus, the categorical description of communities with low sampling effort (e.g., if a community is modular or not) should be done with caution. We recommend evaluating both sampling completeness and taxonomic certainty when conducting bipartite network analyses. Care should also be exercised when using nonrobust descriptors (the four descriptors for parasite taxonomic resolution; modularity for host sampling completeness) when sampling issues are likely to affect a dataset.

Bipartite network analysis is a powerful tool to study the processes structuring interactions in antagonistic ecological communities. In applying the method, we assume that the sampled interactions provide an accurate representation of the actual community. However, acquiring a representative sample may be difficult as not all species are equally abundant or easily identifiable. Two potential sampling issues can compromise the conclusions of bipartite network analyses: failure to capture the full range of interactions of species (sampling completeness) and failure to identify species correctly (taxonomic resolution). These sampling issues are likely to co-occur in community ecology studies. We asked how commonly used descriptors (modularity, nestedness, connectance and specialisation (H ₂ ′)) of bipartite communities are affected by reduced host sampling completeness, parasite taxonomic resolution and their crossed effect. We used a quantitative niche model to generate replicates of simulated weighted bipartite networks that resembled natural host-parasite communities. The combination of both sampling issues had an additive effect on modularity and nestedness. The descriptors were more sensitive to uncertainty in parasite taxonomic resolution than to host sampling completeness. All descriptors in communities capturing less than 70% of correct taxonomic resolution strongly differed from correctly identified communities. When only 10% of parasite taxonomic resolution was retained, modularity and specialisation decreased ∼0.3 and ∼0.1-fold respectively, and nestedness and connectance changed ∼0.7 and ∼3.2-fold respectively. The loss of taxonomic resolution made the confidence intervals of estimates wider. Reduced taxonomic resolution led to smaller size of the communities, which emphasised the larger relative effect of taxonomic resolution on smaller communities. With regards to host sampling completeness, connectance and specialisation were robust, nestedness was reasonably robust (∼0.2-fold overestimation), and modularity was sensitive (∼0.5-fold underestimation). Nonetheless, most of the communities with low resolution for both sampling issues were structurally equivalent to correctly sampled communities (i.e., more modular and less nested than random assemblages). Therefore, modularity and nestedness were useful as categorical rather than quantitative descriptors of communities affected by sampling issues. We recommend evaluating both sampling completeness and taxonomic certainty when conducting bipartite network analyses. We also advise to apply the most robust descriptors in circumstances of unavoidable sampling issues. Open Research statement: we provide permanent and open access links to data sources and replication code in Appendix S1.

For mating-system evolution, individual-level variation is essential. In self-compatible hermaphrodites, individuals may vary in their lifetime propensity for selfing, which consists of individual and environmental components. According to the reproductive assurance hypothesis explaining partial selfing, a key environmental factor is mate availability, which fluctuates with population density. We quantified individual variation in selfing propensity in a hermaphroditic snail by manipulating mate availability, recording mating behaviour, estimating selfing rates from progeny arrays, and measuring female lifetime fitness. We found substantial among-individual variation in selfing propensity, including pure outcrossers, pure selfers, and two types of plastic individuals. This variation only manifested in the laboratory; for the highly dense field population, data suggest full outcrossing. Meanwhile, experimental levels of mate availability (low versus moderate) neither significantly affected selfing propensities nor selfing rates. Instead, selfing propensities had an individual, environment-independent component. Our results imply that selfing propensities are partially heritable and, when selected on, cause mean selfing rates to evolve. We propose that genetic variation in selfing propensities offers a reconciliation between the reproductive assurance hypothesis and its limited empirical support in animals: distributions of selfing propensities vary temporally and spatially, thus obscuring the relationship between population density and realised selfing rates.