Life stage-specific inbreeding depression in long-lived Pinaceae species depends on population connectivity

Inbreeding depression (ID) is a fundamental selective pressure that shapes mating systems and population genetic structures in plants. Although it has been shown that ID varies over the life stages of shorter-lived plants, less is known about how the fitness effects of inbreeding vary across life stages in long-lived species. We conducted a literature survey in the Pinaceae, a tree family known to harbour some of the highest mutational loads ever reported. Using a meta-regression model, we investigated distributions of inbreeding depression over life stages, adjusting for effects of inbreeding levels and the genetic differentiation of populations within species. The final dataset contained 147 estimates of ID across life stages from 41 studies. 44 Fst estimates were collected from 40 peer-reviewed studies for the 18 species to aid genetic differentiation modelling. Partitioning species into fragmented and well-connected groups using Fst resulted in the best way (i.e. trade-off between high goodness-of-fit of the model to the data and reduced model complexity) to incorporate genetic connectivity in the meta-regression analysis. Inclusion of a life stage term and its interaction with the inbreeding coefficient (F) dramatically increased model precision. We observed that the correlation between ID and F was significant at the earliest life stage. Although partitioning of species populations into fragmented and well-connected groups explained little of the between-study heterogeneity, the inclusion of an interaction between life stage and population differentiation revealed that populations with fragmented distributions suffered lower inbreeding depression at early embryonic stages than species with well-connected populations. There was no evidence for increased ID in late life stages in well-connected populations, although ID tended to increase across life stages in the fragmented group. These findings suggest that life stage data should be included in inbreeding depression studies and that inbreeding needs to be managed over life stages in commercial populations of long-lived plants.

Construction of a High-Density Genetic Map of Acca sellowiana (Berg.) Burret, an Outcrossing Species, Based on Two Connected Mapping Populations

Acca sellowiana, known as feijoa or pineapple guava, is a diploid, (2n = 2x = 22) outcrossing fruit tree species native to Uruguay and Brazil. The species stands out for its highly aromatic fruits, with nutraceutical and therapeutic value. Despite its promising agronomical value, genetic studies on this species are limited. Linkage genetic maps are valuable tools for genetic and genomic studies, and constitute essential tools in breeding programs to support the development of molecular breeding strategies. A high-density composite genetic linkage map of A. sellowiana was constructed using two genetically connected populations: H5 (TCO × BR, N = 160) and H6 (TCO × DP, N = 184). Genotyping by sequencing (GBS) approach was successfully applied for developing single nucleotide polymorphism (SNP) markers. A total of 4,921 SNP markers were identified using the reference genome of the closely related species Eucalyptus grandis, whereas other 4,656 SNPs were discovered using a de novo pipeline. The individual H5 and H6 maps comprised 1,236 and 1,302 markers distributed over the expected 11 linkage groups, respectively. These two maps spanned a map length of 1,593 and 1,572 cM, with an average inter-marker distance of 1.29 and 1.21 cM, respectively. A large proportion of markers were common to both maps and showed a high degree of collinearity. The composite map consisted of 1,897 SNPs markers with a total map length of 1,314 cM and an average inter-marker distance of 0.69. A novel approach for the construction of composite maps where the meiosis information of individuals of two connected populations is captured in a single estimator is described. A high-density, accurate composite map based on a consensus ordering of markers provides a valuable contribution for future genetic research and breeding efforts in A. sellowiana. A novel mapping approach based on an estimation of multipopulation recombination fraction described here may be applied in the construction of dense composite genetic maps for any other outcrossing diploid species.

Exotic bifurcations in three connected populations with Allee effect

We consider three connected populations with strong Allee effect, and give a complete classification of the steady state structure of the system with respect to the Allee threshold and the dispersal rate, describing the bifurcations at each critical point where the number of steady states change. One may expect that by increasing the dispersal rate between the patches, the system would become more well-mixed hence simpler. However, we show that it is not always the case, and the number of steady states may (temporarily) increase by increasing the dispersal rate. Besides sequences of pitchfork and saddle-node bifurcations, we find triple-transcritical bifurcations and also a sun-ray shaped bifurcation where twelve steady states meet at a single point then disappear. The major tool of our investigations is a novel algorithm that decomposes the parameter space with respect to the number of steady states and find the bifurcation values using cylindrical algebraic decomposition with respect to the discriminant variety of the polynomial system.

Corridors of tolerance through human-dominated landscapes facilitate dispersal and connectivity between populations of African lions Panthera leo

Globally, little is known about the dispersal abilities of carnivores, their survival in non-protected areas, and the connectivity between protected and non-protected populations. More than a decade of sighting data for 496 known African lions Panthera leo, with 189 individuals engaging in dispersing activities plus an exchange of cross-site information, has provided unique insight into connectivity and survival in unprotected and protected areas in Kenya. In particular, three individuals, across two generations residing solely in unprotected landscapes, demonstrated connectivity between three protected areas that, to our knowledge, have not previously been recognized as harbouring connected populations. These observations suggest that unprotected areas and the human communities that reside in them may successfully create corridors of tolerance that facilitate connectivity and the long-term persistence of lion populations, both within and outside protected areas.

Evolutionary dynamics with game transitions

The environment has a strong influence on a population’s evolutionary dynamics. Driven by both intrinsic and external factors, the environment is subject to continual change in nature. To capture an ever-changing environment, we consider a model of evolutionary dynamics with game transitions, where individuals’ behaviors together with the games that they play in one time step influence the games to be played in the next time step. Within this model, we study the evolution of cooperation in structured populations and find a simple rule: Weak selection favors cooperation over defection if the ratio of the benefit provided by an altruistic behavior, b, to the corresponding cost, c, exceedsk−k′, where k is the average number of neighbors of an individual andk′captures the effects of the game transitions. Even if cooperation cannot be favored in each individual game, allowing for a transition to a relatively valuable game after mutual cooperation and to a less valuable game after defection can result in a favorable outcome for cooperation. In particular, small variations in different games being played can promote cooperation markedly. Our results suggest that simple game transitions can serve as a mechanism for supporting prosocial behaviors in highly connected populations.

Migration alters oscillatory dynamics and promotes survival in connected bacterial populations

Migration influences population dynamics on networks, thereby playing a vital role in scenarios ranging from species extinction to epidemic propagation. While low migration rates prevent local populations from becoming extinct, high migration rates enhance the risk of global extinction by synchronizing the dynamics of connected populations. Here, we investigate this trade-off using two mutualistic strains of E. coli that exhibit population oscillations when co-cultured. In experiments, as well as in simulations using a mechanistic model, we observe that high migration rates lead to in-phase synchronization whereas intermediate migration rates perturb the oscillations and change their period. Further, our simulations predict, and experiments show, that connected populations subjected to more challenging antibiotic concentrations have the highest probability of survival at intermediate migration rates. Finally, we identify altered population dynamics, rather than recolonization, as the primary cause of extended survival.