Bet‐hedging as a complex interaction among developmental instability,environmental heterogeneity,dispersal, and life‐history strategy

One potential evolutionary response to environmental heterogeneity is the production of randomly variable offspring through developmental instability, a type of bet‐hedging. I used an individual‐based, genetically explicit model to examine the evolution of developmental instability. The model considered both temporal and spatial heterogeneity alone and in combination, the effect of migration pattern (stepping stone vs. island), and life‐history strategy. I confirmed that temporal heterogeneity alone requires a threshold amount of variation to select for a substantial amount of developmental instability. For spatial heterogeneity only, the response to selection on developmental instability depended on the life‐history strategy and the form and pattern of dispersal with the greatest response for island migration when selection occurred before dispersal. Both spatial and temporal variation alone select for similar amounts of instability, but in combination resulted in substantially more instability than either alone. Local adaptation traded off against bet‐hedging, but not in a simple linear fashion. I found higher‐order interactions between life‐history patterns, dispersal rates, dispersal patterns, and environmental heterogeneity that are not explainable by simple intuition. We need additional modeling efforts to understand these interactions and empirical tests that explicitly account for all of these factors.     

Dispersal evolution in temporally variable environments: implications for plant range dynamics

Dispersal—the movement of an individual from the site of birth to a different site for reproduction—is an ecological and evolutionary driver of species ranges that shapes patterns of colonization, connectivity, gene flow, and adaptation. In plants, the traits that influence dispersal often vary within and among species, are heritable, and evolve in response to the fitness consequences of moving through heterogeneous landscapes. Spatial and temporal variation in the quality and quantity of habitat are important sources of selection on dispersal strategies across species ranges. While recent reviews have evaluated the interactions between spatial variation in habitat and dispersal dynamics, the extent to which geographic variation in temporal variability can also shape range-wide patterns in dispersal traits has not been synthesized. In this paper, we summarize key predictions from metapopulation models that evaluate how dispersal evolves in response to spatial and temporal habitat variability. Next, we compile empirical data that quantify temporal variability in plant demography and patterns of dispersal trait variation across species ranges to evaluate the hypothesis that higher temporal variability favors increased dispersal at plant range limits. We found some suggestive evidence supporting this hypothesis while more generally identifying a major gap in empirical work evaluating plant metapopulation dynamics across species ranges and geographic variation in dispersal traits. To address this gap, we propose several future research directions that would advance our understanding of the interplay between spatiotemporal variability and dispersal trait variation in shaping the dynamics of current and future species ranges.     

Coalescent and biophysical models of stepping‐stone gene flow in neritid snails

Marine species in the Indo‐Pacific have ranges that can span thousands of kilometres, yet studies increasingly suggest that mean larval dispersal distances are less than historically assumed. Gene flow across these ranges must therefore rely to some extent on larval dispersal among intermediate ‘stepping‐stone’ populations in combination with long‐distance dispersal far beyond the mean of the dispersal kernel. We evaluate the strength of stepping‐stone dynamics by employing a spatially explicit biophysical model of larval dispersal in the tropical Pacific to construct hypotheses for dispersal pathways. We evaluate these hypotheses with coalescent models of gene flow among high‐island archipelagos in four neritid gastropod species. Two of the species live in the marine intertidal, while the other two are amphidromous, living in fresh water but retaining pelagic dispersal. Dispersal pathways predicted by the biophysical model were strongly favoured in 16 of 18 tests against alternate hypotheses. In regions where connectivity among high‐island archipelagos was predicted as direct, there was no difference in gene flow between marine and amphidromous species. In regions where connectivity was predicted through stepping‐stone atolls only accessible to marine species, gene flow estimates between high‐island archipelagos were significantly higher in marine species. Moreover, one of the marine species showed a significant pattern of isolation by distance consistent with stepping‐stone dynamics. While our results support stepping‐stone dynamics in Indo‐Pacific species, we also see evidence for nonequilibrium processes such as range expansions or rare long‐distance dispersal events. This study couples population genetic and biophysical models to help to shed light on larval dispersal pathways.     

The influence of geographical and ecological factors on island beta diversity patterns

Aim To investigate the importance of various island characteristics in determining spatial patterns of variations in beta diversity for various animal groups. Location Analyses are presented for 10 animal groups living on the Aeolian Islands, a volcanic archipelago in the central Mediterranean, near Sicily. Methods Three hypotheses were formulated to explain patterns of beta diversity: the target‐area–distance effect, stepping stone dispersal and island age. Matrices of inter‐island dissimilarities were constructed under each hypothesis and correlated with matrices of faunal dissimilarities using Mantel tests. For the ‘target‐area–distance effect’ hypothesis, inter‐island dissimilarities were calculated using island sizes and distances to nearest mainland areas. For the ‘stepping stone dispersal’ hypothesis, inter‐island distances were measured. Finally, for the ‘island age’ hypothesis, inter‐island dissimilarities were calculated on the basis of the geological age of the islands. Cluster analysis was used to investigate inter‐island faunal relationships. Results Support for a target‐area–distance effect was found only for birds. For these highly mobile animals, inter‐island distances had no significant effects on beta diversity. Birds are known to colonize islands by crossing large sea barriers and thus they can easily reach the Aeolian Islands, which are close to source areas (notably Sicily). Inter‐island distances had a significant role in determining patterns of beta diversity in most invertebrates. For Mollusca, Opiliones, Chilopoda, Heteroptera, coprophagous Scarabaeoidea, and Tenebrionidae, even relatively short distances preclude invertebrates from colonizing an island regularly from the mainland, and most colonization probably results from inter‐island faunal exchanges. Island age was proved to be important only for orthopterans. Main conclusions The origin of most of the Aeolian invertebrate fauna is quite recent, and species appear to have established on the islands predominantly by stepping stone dispersal. Birds, which are highly mobile organisms, follow more direct mainland–island dynamics. As further studies on other islands become available, comparative analyses will confirm whether the factors influencing variations in beta diversity in this study and their relationships with species dispersal ability are consistent across scales and geographical context.     

Evolution of dispersal in a multi‐trophic community context

Much is known about the evolution of dispersal when species interact with their resources or natural enemies, but very little is known about dispersal evolution when species interact with both resources and natural enemies. Here I investigate how the dispersal of an intermediate consumer evolves in response to its interactions with a basal resource and top predator. I find that dispersal evolution is possible even when the consumer species is not directly affected by environmental variability, but rather experiences the consequences that such variability has on its resource and predator. Spatial variation in the consumer's fitness is driven by spatial heterogeneity in resource productivity, which determines whether a predator can colonize a resource‐consumer community. Temporal variation in the consumer's fitness is driven by random disturbances that cause periodic local extinctions of the predator, followed by recolonizations that lead to transient fluctuations in consumer abundance. When spatial variation in resource productivity is low and the predator can colonize all patches in the landscape, there is no spatial variation in consumer fitness but temporal variation in fitness favors the evolution of a dispersal monomorphism. When spatial variation in resource productivity is high and the predator cannot colonize many patches in the landscape, spatial variation in fitness selects against dispersal. In this case, temporal variation can promote the evolution of a dispersal polymorphism with sedentary and mobile phenotypes, but only for certain types of tri‐trophic interactions. This finding underscores the importance of indirect interactions in shaping the evolution of dispersal. While the ecological community can provide a strong selective environment for the evolution of dispersal, the nature of interactions between trophic levels can also impose constraints on evolution.     

Temporal patterns in adult salmon migration timing across southeast Alaska

Pacific salmon migration timing can drive population productivity, ecosystem dynamics, and human harvest. Nevertheless, little is known about long‐term variation in salmon migration timing for multiple species across broad regions. We used long‐term data for five Pacific salmon species throughout rapidly warming southeast Alaska to describe long‐term changes in salmon migration timing, interannual phenological synchrony, relationships between climatic variation and migratory timing, and to test whether long‐term changes in migration timing are related to glaciation in headwater streams. Temporal changes in the median date of salmon migration timing varied widely across species. Most sockeye populations are migrating later over time (11 of 14), but pink, chum, and especially coho populations are migrating earlier than they did historically (16 of 19 combined). Temporal trends in duration and interannual variation in migration timing were highly variable across species and populations. The greatest temporal shifts in the median date of migration timing were correlated with decreases in the duration of migration timing, suggestive of a loss of phenotypic variation due to natural selection. Pairwise interannual correlations in migration timing varied widely but were generally positive, providing evidence for weak region‐wide phenological synchrony. This synchrony is likely a function of climatic variation, as interannual variation in migration timing was related to climatic phenomenon operating at large‐ (Pacific decadal oscillation), moderate‐ (sea surface temperature), and local‐scales (precipitation). Surprisingly, the presence or the absence of glaciers within a watershed was unrelated to long‐term shifts in phenology. Overall, there was extensive heterogeneity in long‐term patterns of migration timing throughout this climatically and geographically complex region, highlighting that future climatic change will likely have widely divergent impacts on salmon migration timing. Although salmon phenological diversity will complicate future predictions of migration timing, this variation likely acts as a major contributor to population and ecosystem resiliency in southeast Alaska.     

Spatial and temporal patterns of larval dispersal in a coral‐reef fish metapopulation: evidence of variable reproductive success

Many marine organisms can be transported hundreds of kilometres during their pelagic larval stage, yet little is known about spatial and temporal patterns of larval dispersal. Although traditional population‐genetic tools can be applied to infer movement of larvae on an evolutionary timescale, large effective population sizes and high rates of gene flow present serious challenges to documenting dispersal patterns over shorter, ecologically relevant, timescales. Here, we address these challenges by combining direct parentage analysis and indirect genetic analyses over a 4‐year period to document spatial and temporal patterns of larval dispersal in a common coral‐reef fish: the bicolour damselfish (Stegastes partitus). At four island locations surrounding Exuma Sound, Bahamas, including a long‐established marine reserve, we collected 3278 individuals and genotyped them at 10 microsatellite loci. Using Bayesian parentage analysis, we identified eight parent‐offspring pairs, thereby directly documenting dispersal distances ranging from 0 km (i.e., self‐recruitment) to 129 km (i.e., larval connectivity). Despite documenting substantial dispersal and gene flow between islands, we observed more self‐recruitment events than expected if the larvae were drawn from a common, well‐mixed pool (i.e., a completely open population). Additionally, we detected both spatial and temporal variation in signatures of sweepstakes and Wahlund effects. The high variance in reproductive success (i.e., ‘sweepstakes’) we observed may be influenced by seasonal mesoscale gyres present in the Exuma Sound, which play a prominent role in shaping local oceanographic patterns. This study documents the complex nature of larval dispersal in a coral‐reef fish, and highlights the importance of sampling multiple cohorts and coupling both direct and indirect genetic methods in order disentangle patterns of dispersal, gene flow and variable reproductive success.     

The genetics of phenotypic plasticity. XIII. Interactions with developmental instability

In a heterogeneous environment, natural selection on a trait can lead to a variety of outcomes, including phenotypic plasticity and bet‐hedging through developmental instability. These outcomes depend on the magnitude and pattern of that heterogeneity and the spatial and temporal distribution of individuals. However, we do not know if and how those two outcomes might interact with each other. I examined the joint evolution of plasticity and instability through the use of an individual‐based simulation in which each could be genetically independent or pleiotropically linked. When plasticity and instability were determined by different loci, the only effect on the evolution of plasticity was the elimination of plasticity as a bet‐hedging strategy. In contrast, the effects on the evolution of instability were more substantial. If conditions were such that the population was likely to evolve to the optimal reaction norm, then instability was disfavored. Instability was favored only when the lack of a reliable environmental cue disfavored plasticity. When plasticity and instability were determined by the same loci, instability acted as a strong limitation on the evolution of plasticity. Under some conditions, selection for instability resulted in maladaptive plasticity. Therefore, before testing any models of plasticity or instability evolution, or interpreting empirical patterns, it is important to know the ecological, life history, developmental, and genetic contexts of trait phenotypic plasticity and developmental instability.     

Linking the spatial scale of environmental variation and the evolution of phenotypic plasticity: selection favors adaptive plasticity in fine-grained environments

Adaptive phenotypic plasticity and adaptive genetic differentiation enable plant lineages to maximize their fitness in response to environmental heterogeneity. The spatial scale of environmental variation relative to the average dispersal distance of a species determines whether selection will favor plasticity, local adaptation, or an intermediate strategy. Habitats where the spatial scale of environmental variation is less than the dispersal distance of a species are fine grained and should favor the expression of adaptive plasticity, while coarse-grained habitats, where environmental variation occurs on spatial scales greater than dispersal, should favor adaptive genetic differentiation. However, there is relatively little information available characterizing the link between the spatial scale of environmental variation and patterns of selection on plasticity measured in the field. I examined patterns of spatial environmental variation within a serpentine mosaic grassland and selection on an annual plant (Erodium cicutarium) within that landscape. Results indicate that serpentine soil patches are a significantly finer-grained habitat than non-serpentine patches. Additionally, selection generally favored increased plasticity on serpentine soils and diminished plasticity on non-serpentine soils. This is the first empirical example of differential selection for phenotypic plasticity in the field as a result of strong differences in the grain of environmental heterogeneity within habitats.     

The rule of "one migrant per generation" and genetic differentiation in subdivided populations

The genetic differentiation in population with migration according island and two-dimensional stepping stone models was studied with simulation methods. It is shown that migration of one or few individuals per generation is insufficient for leveling differences between subpopulations in allele frequencies. Even if migration is estimated as m = 0.5 (exchange of 50 and 500 individuals per generation) statistically significant differences remain at least in the half of populations with insular structure. Spatial heterogeneity disappears completely only if m = 0.7-0.8. In case of two-dimensional step model the level of genetic differentiation is higher and statistically significant heterogeneity remains at all levels of genetic exchange including that which was estimated as m = 1.     

The genetic underpinnings of population cyclicity: establishing expectations for the genetic anatomy of cycling populations

Despite extensive research into the mechanisms underlying population cyclicity, we have little understanding of the impacts of numerical fluctuations on the genetic variation of cycling populations. Thus, the potential implications of natural and anthropogenically‐driven variation in population cycle dynamics on the diversity and evolutionary potential of cyclic populations is unclear. Here, we use Canada lynx Lynx canadensis matrix population models, set up in a linear stepping‐stone, to generate demographic replicates of biologically realistic cycling populations. Overall, increasing cycle amplitude predictably reduced genetic diversity and increased genetic differentiation, with cyclic effects increased by population synchrony. Modest dispersal rates (1–3% of the population) between high and low amplitude cyclic populations did not diminish these effects suggesting that spatial variation in cyclic amplitude should be reflected in patterns of genetic diversity and differentiation at these rates. At high dispersal rates (6%) groups containing only high amplitude cyclic populations had higher diversity and lower differentiation than those mixed with low amplitude cyclic populations. Negative density‐dependent dispersal did not impact genetic diversity, but did homogenize populations by reducing differentiation and patterns of isolation by distance. Surprisingly, temporal changes in diversity and differentiation throughout a cycle were not always consistent with population size. In particular, negative density‐dependent dispersal simultaneously decreased differences in genetic diversity while increasing differences in genetic differentiation between numerical peaks and nadirs. Combined, our findings suggest demographic changes at fine temporal scales can impact genetic variation of interacting populations and provide testable predictions relating population cyclicty to genetic variation. Further, our results suggest that including realistic demographic and dispersal parameters in population genetic models and using information from temporal changes in genetic variation could help to discern complex demographic scenarios and illuminate population dynamics at fine temporal scales.     

A conceptual framework for the spatial analysis of functional trait diversity

Functional trait diversity is a popular tool in modern ecology, mainly used to infer assembly processes and ecosystem functioning. Patterns of functional trait diversity are shaped by ecological processes such as environmental filtering, species interactions and dispersal that are inherently spatial, and different processes may operate at different spatial scales. Adding a spatial dimension to the analysis of functional trait diversity may thus increase our ability to infer community assembly processes and to predict change in assembly processes following disturbance or land‐use change. Richness, evenness and divergence of functional traits are commonly used indices of functional trait diversity that are known to respond differently to large‐scale filters related to environmental heterogeneity and dispersal and fine‐scale filters related to species interactions (competition). Recent developments in spatial statistics make it possible to separately quantify large‐scale patterns (variation in local means) and fine‐scale patterns (variation around local means) by decomposing overall spatial autocorrelation quantified by Moran's coefficient into its positive and negative components using Moran eigenvector maps (MEM). We thus propose to identify the spatial signature of multiple ecological processes that are potentially acting at different spatial scales by contrasting positive and negative components of spatial autocorrelation for each of the three indices of functional trait diversity. We illustrate this approach with a case study from riparian plant communities, where we test the effects of disturbance on spatial patterns of functional trait diversity. The fine‐scale pattern of all three indices was increased in the disturbed versus control habitat, suggesting an increase in local scale competition and an overall increase in unexplained variance in the post‐disturbance versus control community. Further research using simulation modeling should focus on establishing the proposed link between community assembly rules and spatial patterns of functional trait diversity to maximize our ability to infer multiple processes from spatial community structure.     

The genetics of phenotypic plasticity. X. Variation versus uncertainty

Despite the apparent advantages of adaptive plasticity, it is not common. We examined the effects of variation and uncertainty on selection for plasticity using an individual-based computer simulation model. In the model, the environment consisted of a linear gradient of 50 demes with dispersal occurring either before or after selection. Individuals consisted of multiple loci whose phenotypic expression either are affected (plastic) or are not affected (nonplastic) by the environment. Typically, evolution occurred first as genetic differentiation, which was then replaced by the evolution of adaptive plasticity, opposite to the evolutionary trend that is often assumed. Increasing dispersal rates selected for plasticity, if selection occurred before dispersal. If selection occurred after dispersal, the highest plasticity was at intermediate dispersal rates. Temporal variation in the environment occurring after development, but before selection, favored the evolution of plasticity. With dispersal before selection, such temporal variation resulted in hyperplasticity, with a reaction norm much steeper than the optimum. This effect was enhanced with negative temporal autocorrelation and can be interpreted as representing a form of bet hedging. As the number of nonplastic loci increased, plasticity was disfavored due to an increase in the uncertainty of the genomic environment. This effect was reversed with temporal variation. Thus, variation and uncertainty affect whether or not plasticity is favored with different sources of variation-arising from the amount and timing of dispersal, from temporal variation, and even from the genetic architecture underlying the phenotype-having contrasting, interacting, and at times unexpected effects.     

The genetics of phenotypic plasticity. XI. Joint evolution of plasticity and dispersal rate

In a spatially heterogeneous environment, the rate at which individuals move among habitats affects whether selection favors phenotypic plasticity or genetic differentiation, with high dispersal rates favoring trait plasticity. Until now, in theoretical explorations of plasticity evolution, dispersal rate has been treated as a fixed, albeit probabilistic, characteristic of a population, raising the question of what happens when the propensity to disperse and trait plasticity are allowed to evolve jointly. We examined the effects of their joint evolution on selection for plasticity using an individual-based computer simulation model. In the model, the environment consisted of a linear gradient of 50 demes with dispersal occurring either before or after selection. Individuals consisted of loci whose phenotypic expression either are affected by the environment (plastic) or are not affected (nonplastic), plus a locus determining the propensity to disperse. When dispersal rate and trait plasticity evolve jointly, the system tends to dichotomous outcomes of either high trait plasticity and high dispersal, or low trait plasticity and low dispersal. The outcome strongly depended on starting conditions, with high trait plasticity and dispersal favored when the system started at high values for either trait plasticity or dispersal rate (or both). Adding a cost of plasticity tended to drive the system to genetic differentiation, although this effect also depended on initial conditions. Genetic linkage between trait plasticity loci and dispersal loci further enhanced this strong dichotomy in evolutionary outcomes. All of these effects depended on organismal life history pattern, and in particular whether selection occurred before or after dispersal. These results can explain why adaptive trait plasticity is less common than might be expected.     

Effect of migration and environmental heterogeneity on the maintenance of quantitative genetic variation: a simulation study

The paradox of high genetic variation observed in traits under stabilizing selection is a long‐standing problem in evolutionary theory, as mutation rates appear too low to explain observed levels of standing genetic variation under classic models of mutation–selection balance. Spatially or temporally heterogeneous environments can maintain more standing genetic variation within populations than homogeneous environments, but it is unclear whether such conditions can resolve the above discrepancy between theory and observation. Here, we use individual‐based simulations to explore the effect of various types of environmental heterogeneity on the maintenance of genetic variation (V_A) for a quantitative trait under stabilizing selection. We find that V_A is maximized at intermediate migration rates in spatially heterogeneous environments and that the observed patterns are robust to changes in population size. Spatial environmental heterogeneity increased variation by as much as 10‐fold over mutation–selection balance alone, whereas pure temporal environmental heterogeneity increased variance by only 45% at max. Our results show that some combinations of spatial heterogeneity and migration can maintain considerably more variation than mutation–selection balance, potentially reconciling the discrepancy between theoretical predictions and empirical observations. However, given the narrow regions of parameter space required for this effect, this is unlikely to provide a general explanation for the maintenance of variation. Nonetheless, our results suggest that habitat fragmentation may affect the maintenance of V_A and thereby reduce the adaptive capacity of populations.     

Nonrandom larval dispersal can steepen marine clines

Sharp and stable clinal variation is enigmatic when found in species with high gene flow. Classical population genetic models treat gene flow as a random homogenizing force countering local adaptation across habitat discontinuities. Under this view, dispersal over large spatial scales will lower the effectiveness of adaptation by natural selection at finer spatial scales. Thus, random gene flow will create a shallow phenotypic cline across an ecotone in response to a steep selection gradient. In sedentary marine species that disperse primarily as larvae, nonrandom dispersal patterns are expected due to coastal hydrodynamics. Surprisingly sharp phenotypic and genotypic clines have been documented in marine species with high gene flow. We are interested in the extent to which nonrandom dispersal could accentuate such clines. We model a linear species range in which populations have stable and uniform densities along a selection gradient; in contrast to random dispersal, convergent advection of larvae can amplify phenotypic differentiation if coupled with a semipermeable dispersal barrier in the convergence zone. The migration load caused by directional dispersal pushes the phenotypic mean away from the local trait optimum in downstream populations, that is, near the convergence zone. A dispersal barrier is possible as a result of colliding currents if the water and larvae are mostly displaced offshore, away from suitable settlement habitat. Disjunctions in a quantitative trait were enlarged in the convergence zone by faster current flows or a more complete dispersal barrier. With advection of larvae per generation one-third as far as the average dispersal distance by diffusion, convergence on a dispersal barrier with 40% permeability generated a trait disjunction across the convergence zone of two phenotypic standard deviations. Without directional dispersal, similar clines also developed across a habitat gap, where population density was low, or across dispersal barriers with less than 1% permeability. These findings suggest that the types of hydrographic phenomena often associated with marine transition zones can strongly affect the balance between gene flow and selection and generate surprisingly steep clines given the large-scale gene flow expected from larvae.     

Bet-hedging via dispersal aids the evolution of plastic responses to unreliable cues

Adaptive plasticity is expected to evolve when informative cues predict environmental variation. However, plastic responses can be maladaptive even when those cues are informative, if prediction mistakes are shared across members of a generation. These fitness costs can constrain the evolution of plasticity when initial plastic mutants use of cues of only moderate reliability. Here, we model the barriers to the evolution of plasticity produced by these constraints and show that dispersal across a metapopulation can overcome them. Constraints are also lessened, though not eliminated, when plastic responses are free to evolve gradually and in concert with increased reliability. Each of these factors be viewed as a form of bet-hedging: by lessening correlations in the fates of relatives, dispersal acts as diversifying bet-hedging, while producing submaximal responses to a cue can be understood as a conservative bet-hedging strategy. While poor information may constrain the evolution of plasticity, the opportunity for bet-hedging may predict when that constraint can be overcome.     

Population and evolutionary dynamics in spatially structured seasonally varying environments

Increasingly imperative objectives in ecology are to understand and forecast population dynamic and evolutionary responses to seasonal environmental variation and change. Such population and evolutionary dynamics result from immediate and lagged responses of all key life‐history traits, and resulting demographic rates that affect population growth rate, to seasonal environmental conditions and population density. However, existing population dynamic and eco‐evolutionary theory and models have not yet fully encompassed within‐individual and among‐individual variation, covariation, structure and heterogeneity, and ongoing evolution, in a critical life‐history trait that allows individuals to respond to seasonal environmental conditions: seasonal migration. Meanwhile, empirical studies aided by new animal‐tracking technologies are increasingly demonstrating substantial within‐population variation in the occurrence and form of migration versus year‐round residence, generating diverse forms of ‘partial migration’ spanning diverse species, habitats and spatial scales. Such partially migratory systems form a continuum between the extreme scenarios of full migration and full year‐round residence, and are commonplace in nature. Here, we first review basic scenarios of partial migration and associated models designed to identify conditions that facilitate the maintenance of migratory polymorphism. We highlight that such models have been fundamental to the development of partial migration theory, but are spatially and demographically simplistic compared to the rich bodies of population dynamic theory and models that consider spatially structured populations with dispersal but no migration, or consider populations experiencing strong seasonality and full obligate migration. Second, to provide an overarching conceptual framework for spatio‐temporal population dynamics, we define a ‘partially migratory meta‐population’ system as a spatially structured set of locations that can be occupied by different sets of resident and migrant individuals in different seasons, and where locations that can support reproduction can also be linked by dispersal. We outline key forms of within‐individual and among‐individual variation and structure in migration that could arise within such systems and interact with variation in individual survival, reproduction and dispersal to create complex population dynamics and evolutionary responses across locations, seasons, years and generations. Third, we review approaches by which population dynamic and eco‐evolutionary models could be developed to test hypotheses regarding the dynamics and persistence of partially migratory meta‐populations given diverse forms of seasonal environmental variation and change, and to forecast system‐specific dynamics. To demonstrate one such approach, we use an evolutionary individual‐based model to illustrate that multiple forms of partial migration can readily co‐exist in a simple spatially structured landscape. Finally, we summarise recent empirical studies that demonstrate key components of demographic structure in partial migration, and demonstrate diverse associations with reproduction and survival. We thereby identify key theoretical and empirical knowledge gaps that remain, and consider multiple complementary approaches by which these gaps can be filled in order to elucidate population dynamic and eco‐evolutionary responses to spatio‐temporal seasonal environmental variation and change.     

Evolution of Pathogen Specialisation in a Host Metapopulation: Joint Effects of Host and Pathogen Dispersal

Metapopulation processes are important determinants of epidemiological and evolutionary dynamics in host-pathogen systems, and are therefore central to explaining observed patterns of disease or genetic diversity. In particular, the spatial scale of interactions between pathogens and their hosts is of primary importance because migration rates of one species can affect both spatial and temporal heterogeneity of selection on the other. In this study we developed a stochastic and discrete time simulation model to specifically examine the joint effects of host and pathogen dispersal on the evolution of pathogen specialisation in a spatially explicit metapopulation. We consider a plant-pathogen system in which the host metapopulation is composed of two plant genotypes. The pathogen is dispersed by air-borne spores on the host metapopulation. The pathogen population is characterised by a single life-history trait under selection, the infection efficacy. We found that restricted host dispersal can lead to high amount of pathogen diversity and that the extent of pathogen specialisation varied according to the spatial scale of host-pathogen dispersal. We also discuss the role of population asynchrony in determining pathogen evolutionary outcomes.     

KIN-STRUCTURED COLONIZATION AND SMALL-SCALE GENETIC DIFFERENTIATION IN SILENE DIOICA

We investigated the genetic structure of a single island population of the dioecious plant Silene dioica in the Skeppsvik Archipelago, Umeå, Sweden. The population is less than 10 years old and consists of approximately 700 individuals growing within an area of about 200 m². Despite the small scale of the study, levels of genetic differentiation among contiguous patches are greater than or comparable to what is observed over larger scales in the archipelago. The results suggest that the small-scale structuring occurs during population expansion, soon after island colonization, and that the observed patterns of genetic differentiation can be attributed to the population being substructured into family groups. This family structure results from kin-structured dispersal processes (colonization and migration) as the population expands over the island. As plant densities increase over time, either spatial fusion or temporal fusion of patches reduce the among patch variation. These processes, however, do not completely eradicate the genetic differentiation established by the kin-structured dispersal processes. We discuss some implications of kin structuring for evolution through either kin or interdemic selection.