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In eusocial species, some individuals sacrifice their own reproduction for the benefit of others. It has been argued that the evolution of sterile helpers in eusocial insects requires synergistic efficiency gains through cooperation that are uncommon in cooperatively breeding vertebrates and that this precludes a universal ecological explanation of social systems with alloparental care. In contrast, using a model that incorporates realistic ecological mechanisms of population regulation, we show here that constraints on independent breeding (through nest-site limitation and dispersal mortality) eliminate any need for synergistic efficiency gains: sterile helpers may evolve even if they are relatively inefficient at rearing siblings, reducing their colony’s per-capita productivity. Our approach connects research fields by using hypotheses developed for cooperative breeding to explain the evolution of eusociality. The results suggest that these hypotheses may apply more generally than previously thought.
How to define and use the concept of inclusive fitness is a contentious topic in evolutionary theory. Inclusive fitness can be used to calculate selection on a focal gene, but it is also applied to whole organisms. Individuals are then predicted to appear designed as if to maximize their inclusive fitness, provided that certain conditions are met (formally when interactions between individuals are ‘additive’). Here we argue that applying the concept of inclusive fitness to organisms is justified under far broader conditions than previously shown, but only if it is appropriately defined. Specifically, we propose that organisms should maximize the sum of their offspring (including any accrued due to the behaviour/phenotype of relatives), plus any effects on their relatives' offspring production, weighted by relatedness. By contrast, most theoreticians have argued that a focal individual's inclusive fitness should exclude any offspring accrued due to the behaviour of relatives. Our approach is based on the notion that long-term evolution follows the genome's ‘majority interest’ of building coherent bodies that are efficient ‘vehicles’ for gene propagation. A gene favoured by selection that reduces the propagation of unlinked genes at other loci (e.g. meiotic segregation distorters that lower sperm production) is eventually neutralized by counter-selection throughout the rest of the genome. Most phenotypes will therefore appear as if designed to maximize the propagation of any given gene in a focal individual and its relatives.
In 1948, Angus Bateman presented experiments and concepts that remain influential and debated in sexual selection. The Bateman gradient relates reproductive success to mate number, and Bateman presented this as the cause of intra-masculine selection. A deeper causal level was subsequently asserted: that the ultimate cause of sex differences in Bateman gradients is the sex difference in gamete numbers, an argument that remains controversial and without mathematical backup. Here I develop models showing how asymmetry in gamete numbers alone can generate steeper Bateman gradients in males. This conclusion remains when the further asymmetry of internal fertilisation is added to the model and fertilisation is efficient. Strong gamete limitation can push Bateman gradients towards equality under external fertilisation and reverse them under internal fertilisation. Thus, this study provides a mathematical formalisation of Bateman’s brief verbal claim, while demonstrating that the link between gamete number and Bateman gradients is not inevitable nor trivial.
As companion dogs spend most of their lives with humans, the human–dog relationship and owner temperament may affect the dog behavior. In this study (n = 440), we investigated the relationship between the dog owner temperament (ATQ-R), owner-perceived dog–owner relationship (MDORS) and the dog behavior in three behavioral tests: the object-choice test, the unsolvable task, and the cylinder test. Dog owner temperament influenced the dog–owner relationship. Owners with high negative affectivity showed higher emotional closeness and perceived costs of their dog, whereas owners with high effortful control showed lower emotional closeness and perceived costs. Higher dog activity during the behavioral tests was also connected with owner-perceived lower emotional closeness. Furthermore, dog breed group modulated the connection between the owner temperament and dog behavior. Owner’s high negative affectivity correlated with herding dogs’ lower scores in the object choice test, while the behavior of primitive type dogs was unaffected by the owner temperament. Our results confirm that human characteristics are associated with the owner-reported dog–owner relationship, and owner temperament may have a modulatory effect on the dog social and cognitive behavior depending on the dog breed group, which should be investigated further.
A long-standing problem in evolutionary theory is to clarify in what sense (if any) natural selection cumulatively improves the design of organisms. Various concepts, such as fitness and inclusive fitness, have been proposed to resolve this problem. In addition, there have been attempts to replace the original problem with more tractable questions such as whether a given gene or trait is favoured by selection. Here we ask what theoretical properties the concept fitness should possess to encapsulate the improvement criterion required to talk meaningfully about adaptive evolution. We argue that natural selection tends to shape phenotypes based on the causal properties of individuals, and that this tendency is therefore best captured by a fitness concept that focusses on these properties. We highlight a fitness concept which meets this role under broad conditions, but requires adjustments in our conceptual understanding of adaptive evolution. These adjustments combine elements of Dawkinsian gene selectionism and Egbert Leigh’s “parliament of genes”.
Dogs process faces and emotional expressions much like humans, but the time windows important for face processing in dogs are largely unknown. By combining our non-invasive electroencephalography (EEG) protocol on dogs with machine-learning algorithms, we show category-specific dog brain responses to pictures of human and dog facial expressions, objects, and phase-scrambled faces. We trained a support vector machine classifier with spatiotemporal EEG data to discriminate between responses to pairs of images. The classification accuracy was highest for humans or dogs vs. scrambled images, with most informative time intervals of 100–140 ms and 240–280 ms. We also detected a response sensitive to threatening dog faces at 30–40 ms; generally, responses differentiating emotional expressions were found at 130–170 ms, and differentiation of faces from objects occurred at 120–130 ms. The cortical sources underlying the highest-amplitude EEG signals were localized to the dog visual cortex.