The role of migration in the genetic structure of populations in temporally and spatially varying environments II. Island Models

The Island Model introduced by Sewall Wright (1951) has proven to be a useful construction for studying the interaction of genetic drift, population subdivision, and mutation. Interest in the model has recently increased because of its relevance to certain questions involving the rate of differentiation of sub-populations under the neutral allele hypothesis (e.g., Smith, 1970; Latter, 1973). It is perhaps the only realistic population structure in which the test for neutrality proposed by Lewontin and Krakauer (1973) is valid (Lewontin and Krakauer, 1975). If data from natural populations is to be compared to the predictions of the Island Model, it is desirable to have an alternative model with the same migration pattern but with natural selection operating. In this paper one such model will be introduced where the stochastic element comes from random fluctuations in the environment rather than from genetic drift. The model is a direct extension of the one in the previous paper in this series (Gillespie, 1975) which dealt with a population which is subdivided into two patches with restricted migration between them.     

Coexistence and emergent neutrality generate synchrony among competitors in fluctuating environments

Many competitive communities exhibit a puzzling amount of species diversity. In this study, we model a community of symmetric competitors in a fluctuating environment. We use biologically realistic temperature-dependent growth curves with a widely hypothesized trade-off between maximum growth and nice breadth to control the shapes of the curves of different species. We perform three analyses of the community dynamics to investigate the role of environmental fluctuations in community composition and species diversity. We initiate communities with equal abundances of all species and randomize the temperature fluctuations so that there is no correlation between species responses, only noise. We initiate single populations and allow other species to randomly invade the community. We also knock out extant species one by one from an established community and allow them to reinvade after the remaining species have adjusted. We find that competitors with sufficiently different temperature niches coexist via temporal niche differentiation. We also find long-term persistence of species that are very similar to a dominant competitor. This creates communities with species clumped along a temperature niche axis, with stable coexistence between groups and near neutrality within groups. The near neutrality results in interspecific synchrony within the groups, providing an explanation for the maintenance of high diversity in competitive communities where synchrony is commonly observed.     

Demographic strategies of plant invaders in temporally varying environments

Plant populations may have evolved different demographic strategies to cope with temporal environmental variation. According to the demographic buffering hypothesis, vital rates that are most critical to population persistence are buffered against environmental variation and vary little over time, whereas the demographic lability hypothesis suggests that populations may track and benefit from environmental variation. While the hypotheses of demographic strategies have been widely tested in plant and animal species, they have not been explicitly examined for invasive plants, or in relation to different modelling methods (deterministic vs. stochastic). Here, we tested the demographic buffering and lability hypotheses for 23 populations of eight invasive plant species in relation to life form (woody vs. herbaceous species) and population growth rate using deterministic and stochastic modelling methods, and absolute and relative scales. We found that conclusions of demographic strategies depended on scale, with an absolute scale resulting in stronger negative correlations between the variability and importance of vital rates (i.e., buffering) than a relative scale. Conclusions of demographic strategies were also affected by life form that interacted with method. The populations of woody invaders exhibited buffering regardless of the method used, while for the populations of herbaceous species, deterministic calculations suggested buffering and stochastic calculations suggested lability. Overall, our findings emphasise the role of life form and methodological issues that need to be considered when exploring demographic strategies in fluctuating environments.     

A framework to compare theoretical predictions on trait evolution in temporally varying environments under different life cycles

Predicting the evolution of traits such as dispersal or local adaptation, in a variable environment is an important issue in theoretical evolutionary ecology. With concepts such as hard selection vs. soft selection or fine-grained vs. coarse-grained environmental variability, this issue has attracted much attention, and yet different models seldom agree on qualitative predictions about, e.g. the evolution of generalist or specialist strategies, or the occurrence of stabilizing or disruptive selection on studied traits.Here, I investigate the effect of the order of events in the life cycle on trait evolution in a spatially heterogeneous, temporally varying landscape using a Wright–Fisher island model. I first develop a methodological framework allowing for different life cycles. Then I illustrate the importance of life cycles on selection regimes by looking more closely at the evolution of local adaptation.Model results show that the occurrence of disruptive selection and bi- or tristability mainly depends on the life cycle, the convexity of the trade-off behind local adaptation, the immigration rate, and the autocorrelation in patch state. With the same forces driving the evolution of local adaptation, different life cycles induce different evolutionary outcomes. Model results highlight the importance of accounting for life cycle specificities when attempting to predict the effects of the environment on evolutionarily selected trait values, as well as the need to check the robustness of evolutionary model conclusions against modifications of the life cycle.     

Evolution of dispersal in spatially and temporally variable environments: The importance of life cycles

Spatiotemporal variability of the environment is bound to affect the evolution of dispersal, and yet model predictions strongly differ on this particular effect. Recent studies on the evolution of local adaptation have shown that the life cycle chosen to model the selective effects of spatiotemporal variability of the environment is a critical factor determining evolutionary outcomes. Here, we investigate the effect of the order of events in the life cycle on the evolution of unconditional dispersal in a spatially heterogeneous, temporally varying landscape. Our results show that the occurrence of intermediate singular strategies and disruptive selection are conditioned by the temporal autocorrelation of the environment and by the life cycle. Life cycles with dispersal of adults versus dispersal of juveniles, local versus global density regulation, give radically different evolutionary outcomes that include selection for total philopatry, evolutionary bistability, selection for intermediate stable states, and evolutionary branching points. Our results highlight the importance of accounting for life‐cycle specifics when predicting the effects of the environment on evolutionarily selected trait values, such as dispersal, as well as the need to check the robustness of model conclusions against modifications of the life cycle.     

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.     

A spatially and temporally restricted mouse model of soft tissue sarcoma

Soft tissue sarcomas are mesenchymal tumors that are fatal in approximately one-third of patients. To explore mechanisms of sarcoma pathogenesis, we have generated a mouse model of soft tissue sarcoma. Intramuscular delivery of an adenovirus expressing Cre recombinase in mice with conditional mutations in Kras and Trp53 was sufficient to initiate high-grade sarcomas with myofibroblastic differentiation. Like human sarcomas, these tumors show a predilection for lung rather than lymph node metastasis. Using this model, we showed that a prototype handheld imaging device can identify residual tumor during intraoperative molecular imaging. Deletion of the Ink4a-Arf locus (Cdkn2a), but not Bak1 and Bax, could substitute for mutation of Trp53 in this model. Deletion of Bak1 and Bax, however, was able to substitute for mutation of Trp53 in the development of sinonasal adenocarcinoma. Therefore, the intrinsic pathway of apoptosis seems sufficient to mediate p53 tumor suppression in an epithelial cancer, but not in this model of soft tissue sarcoma.     

Mesophyll conductance variability of rice aquaporin knockout lines at different growth stages and growing environments

The plasma membrane subfamily of aquaporins [plasma membrane intrinsic proteins (PIPs)], which facilitates the CO₂ diffusion across membranes, is proposed to play an important role in mesophyll conductance to CO₂ (g_m), a major limiting factor of photosynthesis. However, recent studies implied no causal relationship between g_m and PIPs because they failed to repeat the previous observed differences in g_m between PIP knockout lines and their wild-type. The contrasting results on the role of PIPs in g_m were interpreted as the different growth conditions among studies, which has never been tested. Here, we assessed whether the differences in g_m between wild-type and PIP knockout lines, Ospip1;1, Ospip1;2 and Ospip2;1, varied with growth condition (field versus pot condition) and growth stages in rice. Under field conditions, no differences were observed in plant performance, photosynthetic rate (A) and g_m between PIP knockout lines and the wild-type. However, in agreement with previous studies, two out of three knockout lines showed significant declines in tiller number, plant height, A and g_m under pot conditions. Moreover, we found that the differences in A and g_m between PIP knockout lines and the wild-type varied with the growth stage of the plants. Our results showed that the differences in g_m between PIP knockout lines and wild-type were depending on the growth environments and stage of the plants, and further efforts are required to reveal the underlying mechanisms.     

Quantifying the effects of migration and mutation on adaptation and demography in spatially heterogeneous environments

How do mutation and gene flow influence population persistence, niche expansion and local adaptation in spatially heterogeneous environments? In this article, we analyse a demographic and evolutionary model of adaptation to an environment containing two habitats in equal frequencies, and we bridge the gap between different theoretical frameworks. Qualitatively, our model yields four qualitative types of outcomes: (i) global extinction of the population, (ii) adaptation to one habitat only, but also adaptation to both habitats with, (iii) specialized phenotypes or (iv) with generalized phenotypes, and we determine the conditions under which each equilibrium is reached. We derive new analytical approximations for the local densities and the distributions of traits in each habitat under a migration–selection–mutation balance, compute the equilibrium values of the means, variances and asymmetries of the local distributions of phenotypes, and contrast the effects of migration and mutation on the evolutionary outcome. We then check our analytical results by solving our model numerically, and also assess their robustness in the presence of demographic stochasticity. Although increased migration results in a decrease in local adaptation, mutation in our model does not influence the values of the local mean traits. Yet, both migration and mutation can have dramatic effects on population size and even lead to metapopulation extinction when selection is strong. Niche expansion, the ability for the population to adapt to both habitats, can also be prevented by small migration rates and a reduced evolutionary potential characterized by rare mutation events of small effects; however, niche expansion is otherwise the most likely outcome. Although our results are derived under the assumption of clonal reproduction, we finally show and discuss the links between our model and previous quantitative genetics models.     

A different look at the quality of modeled three-dimensional protein structures

Measuring the accuracy of protein three-dimensional structures is one of the most important problems in protein structure prediction. For structure-based drug design, the accuracy of the binding site is far more important than the accuracy of any other region of the protein. We have developed an automated method for assessing the quality of a protein model by focusing on the set of residues in the small molecule binding site. Small molecule binding sites typically involve multiple regions of the protein coming together in space, and their accuracy has been observed to be sensitive to even small alignment errors. In addition, ligand binding sites contain the critical information required for drug design, making their accuracy particularly important. We analyzed the accuracy of the binding sites on two sets of protein models: the predictions submitted by the top-performing CASP7 groups, and the models generated by four widely used homology modeling packages. The results of our CASP7 analysis significantly differ from the previous findings, implying that the binding site measure does not correlate with the traditional model quality measures used in the structure prediction benchmarks. For the modeling programs, the resolution of binding sites is extremely sensitive to the degree of sequence homology between the query and the template, even when the most accurate alignments are used in the homology modeling process.     

Towards the integration of spatially and temporally resolved murine gene expression databases

Several large-scale projects are evaluating gene expression in the mouse brain, both spatially and temporally. These range from projects that cover a broad spectrum of genes and developmental stages to those with high-spatial resolution and gene coverage but for only a single developmental stage. Each project contains its own self-consistent data set and tools for analysis and mining. Preliminary efforts are under way to construct tools and an infrastructure with which the data from across these different projects can be statistically pooled and analyzed. However, many obstacles remain, and these must be addressed and overcome soon if we are to unify the data sets, otherwise the preliminary efforts will be wasted. Here, the various projects for collecting and mining this information are reviewed, some challenges in data set comparisons are discussed, and some basic proposals are made for overcoming the challenges.     

Diversification in temporally heterogeneous environments: effect of the grain in experimental bacterial populations

Although theory established the necessary conditions for diversification in temporally heterogeneous environments, empirical evidence remains controversial. One possible explanation is the difficulty of designing experiments including the relevant range of temporal grains and the appropriate environmental trade-offs. Here, we experimentally explore the impact of the grain on the diversification of the bacterium Pseudomonas fluorescens SBW25 in a temporally fluctuating environment by including 20 different pairs of environments and four temporal grains. In general, higher levels of diversity were observed at intermediate temporal grains. This resulted in part from the enhanced capacity of disruptive selection to generate negative genotypic correlations in performance at intermediate grains. However, the evolution of reciprocal specialization was an uncommon outcome. Although the temporal heterogeneity is in theory less powerful than the spatial heterogeneity to generate and maintain the diversity, our results show that diversification under temporal heterogeneity is possible provided appropriate environmental grains.     

Stochastic population growth in spatially heterogeneous environments: the density-dependent case

Journal of Mathematical Biology - This work is devoted to studying the dynamics of a structured population that is subject to the combined effects of environmental stochasticity, competition for...     

Reproductive success in varying light environments: direct and indirect effects of light on plants and pollinators

Plant populations often exist in spatially heterogeneous environments. Light level can directly affect plant reproductive success through resource availability or by altering pollinator behavior. It can also indirectly influence reproductive success by determining floral display size which may in turn influence pollinator attraction. We evaluated direct and indirect effects of light availability and measured phenotypic selection on phenological traits that may enhance pollen receipt in the insect-pollinated herb Campanulastrum americanum. In a natural population, plants in the sun had larger displays and received 7 times more visits than plants in the shade. Using experimental arrays to separate the direct effects of irradiance on insects from their response to display size, we found more visits to plants in the sun than in the shade, but no association between number of visits each flower received and display size. Plants in the sun were not pollen limited but pollen-augmented shade flowers produced 50% more seeds than open-pollinated flowers. Phenological traits, which may influence pollen receipt, were not under direct selection in the sun. However, earlier initiation and a longer duration of flowering were favored in the shade, which may enhance visitation in this pollen-limited habitat.