Bolder Takes All? The Behavioral Dimension of Biogeography

Animal personality can be seen as behavioral polymorphism that could play a direct and active role in driving evolutionary pathways. We argue here that consistent individual differences in key personality traits affecting dispersal and other density-dependent processes have provided substantial contributions to molding biogeographic patterns. Building upon opportunities recently opened by genomics and other novel approaches, we explore the hypothesis that Pleistocene range expansions, island colonizations, and other historical biogeographic processes could have been promoted by non-random samples of behavioral types of the founder populations. We provide context and testable hypotheses, based on case studies, that could bring new implications to our understanding of the processes shaping spatial and temporal patterns of variation in animal biodiversity.

No Evidence for Activity Adjustment in Response to Increased Density in Daphnia magna

Increased population density may lead to a decrease in energy available for growth and reproduction via effects on the activity level of individuals. Whilst this may be of particular importance for organisms that compete for defendable resources and/or have a high frequency of social interactions, it is less obvious how individual activity should covary with population density when food resources are not defendable or direct interactions among individuals are negligible. Based on observations that there is a general negative relationship between population density and metabolism it has been suggested that organisms actively reduce activity under increased density to accommodate an expected decrease in food availability. However, in the absence of direct activity measurements the validity of this hypothesis is unclear. Here we test for such anticipatory adjustments of activity levels in the planktonic cladoceran Daphnia magna Straus, a filter feeder whose food resources are not defendable, meaning that density responses can be evaluated in the absence of direct interactions. We tested for changes in activity in response to two separate density cues, one being the direct physical and visual stimuli resulting from being in the vicinity of conspecifics (‘direct density experiment’), and the other being the detection of olfactory cues in their environment (‘olfactory cue experiment’). Ten genetically distinct clones were used to evaluate the potential for genetic variation in these responses. Our measures of activity were highly repeatable, and there was significant variation in activity among clones. Furthermore, this clonal variation was consistent in the ‘direct density’ and ‘olfactory cue’ experiments. The estimated evolvability of the trait (1.3–3.2%) was within the range typically observed in behavioural traits. However, there was no indication that the activity level of individuals respond to population density, either directly to actual density or to olfactory cues representing high density. In this case, the energetic influence of density on population dynamics is sufficiently described by effects on per capita resource availability.

Panmictic and Clonal Evolution on a Single Patchy Resource Produces Polymorphic Foraging Guilds

We develop a stochastic, agent-based model to study how genetic traits and experiential changes in the state of agents and available resources influence individuals’ foraging and movement behaviors. These behaviors are manifest as decisions on when to stay and exploit a current resource patch or move to a particular neighboring patch, based on information of the resource qualities of the patches and the anticipated level of intraspecific competition within patches. We use a genetic algorithm approach and an individual’s biomass as a fitness surrogate to explore the foraging strategy diversity of evolving guilds under clonal versus hermaphroditic sexual reproduction. We first present the resource exploitation processes, movement on cellular arrays, and genetic algorithm components of the model. We then discuss their implementation on the Nova software platform. This platform seamlessly combines the dynamical systems modeling of consumer-resource interactions with agent-based modeling of individuals moving over a landscapes, using an architecture that lays transparent the following four hierarchical simulation levels: 1.) within-patch consumer-resource dynamics, 2.) within-generation movement and competition mitigation processes, 3.) across-generation evolutionary processes, and 4.) multiple runs to generate the statistics needed for comparative analyses. The focus of our analysis is on the question of how the biomass production efficiency and the diversity of guilds of foraging strategy types, exploiting resources over a patchy landscape, evolve under clonal versus random hermaphroditic sexual reproduction. Our results indicate greater biomass production efficiency under clonal reproduction only at higher population densities, and demonstrate that polymorphisms evolve and are maintained under random mating systems. The latter result questions the notion that some type of associative mating structure is needed to maintain genetic polymorphisms among individuals exploiting a common patchy resource on an otherwise spatially homogeneous landscape.

Molecular tools and bumble bees: revealing hidden details of ecology and evolution in a model system

Bumble bees are a longstanding model system for studies on behaviour, ecology and evolution, due to their well-studied social lifestyle, invaluable role as wild and managed pollinators, and ubiquity and diversity across temperate ecosystems. Yet despite their importance, many aspects of bumble bee biology have remained enigmatic until the rise of the genetic and, more recently, genomic eras. Here, we review and synthesize new insights into the ecology, evolution and behaviour of bumble bees that have been gained using modern genetic and genomic techniques. Special emphasis is placed on four areas of bumble bee biology: the evolution of eusociality in this group, population-level processes, large-scale evolutionary relationships and patterns, and immunity and resistance to pesticides. We close with a prospective on the future of bumble bee genomics research, as this rapidly advancing field has the potential to further revolutionize our understanding of bumble bees, particularly in regard to adaptation and resilience. Worldwide, many bumble bee populations are in decline. As such, throughout the review, connections are drawn between new molecular insights into bumble bees and our understanding of the causal factors involved in their decline. Ongoing and potential applications to bumble bee management and conservation are also included to demonstrate how genetics- and genomics-enabled research aids in the preservation of this threatened group.