Fundulus as the premier teleost model in environmental biology: opportunities for new insights using genomics

A strong foundation of basic and applied research documents that the estuarine fish Fundulus heteroclitus and related species are unique laboratory and field models for understanding how individuals and populations interact with their environment. In this paper we summarize an extensive body of work examining the adaptive responses of Fundulus species to environmental conditions, and describe how this research has contributed importantly to our understanding of physiology, gene regulation, toxicology, and ecological and evolutionary genetics of teleosts and other vertebrates. These explorations have reached a critical juncture at which advancement is hindered by the lack of genomic resources for these species. We suggest that a more complete genomics toolbox for F. heteroclitus and related species will permit researchers to exploit the power of this model organism to rapidly advance our understanding of fundamental biological and pathological mechanisms among vertebrates, as well as ecological strategies and evolutionary processes common to all living organisms.     

Adaptive evolution in ecological communities

Understanding how natural selection drives evolution is a key challenge in evolutionary biology. Most studies of adaptation focus on how a single environmental factor, such as increased temperature, affects evolution within a single species. The biological relevance of these experiments is limited because nature is infinitely more complex. Most species are embedded within communities containing many species that interact with one another and the physical environment. To understand the evolutionary significance of such ecological complexity, experiments must test the evolutionary impact of interactions among multiple species during adaptation. Here we highlight an experiment that manipulates species composition and tracks evolutionary responses within each species, while testing for the mechanisms by which species interact and adapt to their environment. We also discuss limitations of previous studies of adaptive evolution and emphasize how an experimental evolution approach can circumvent such shortcomings. Understanding how community composition acts as a selective force will improve our ability to predict how species adapt to natural and human-induced environmental change.     

Predicting protein-protein interaction by searching evolutionary tree automorphism space

MOTIVATION: Uncovering the protein-protein interaction network is a fundamental step in the quest to understand the molecular machinery of a cell. This motivates the search for efficient computational methods for predicting such interactions. Among the available predictors are those that are based on the co-evolution hypothesis "evolutionary trees of protein families (that are known to interact) are expected to have similar topologies". Many of these methods are limited by the fact that they can handle only a small number of protein sequences. Also, details on evolutionary tree topology are missing as they use similarity matrices in lieu of the trees. RESULTS: We introduce MORPH, a new algorithm for predicting protein interaction partners between members of two protein families that are known to interact. Our approach can also be seen as a new method for searching the best superposition of the corresponding evolutionary trees based on tree automorphism group. We discuss relevant facts related to the predictability of protein-protein interaction based on their co-evolution. When compared with related computational approaches, our method reduces the search space by approximately 3 x 10(5)-fold and at the same time increases the accuracy of predicting correct binding partners.     

How to Identify and Interpret Evolutionary Tree Diagrams

Evolutionary trees are key tools for modern biology and are commonly portrayed in textbooks to promote learning about biological evolution. However, many people have difficulty in understanding what evolutionary trees are meant to portray. In fact, some ideas that current professional biologists depict with evolutionary trees are neither clearly defined nor conveyed to students. To help biology teachers and students learn how to more deeply interpret, understand and gain knowledge from diagrams that represent ancestor–descendant relationships and evolutionary lineages, we describe the different rooted and unrooted evolutionary tree visualisations and explain how they are best read. Examples from a study of tree-shaped diagrams in the journal Science are used to illustrate how to distinguish evolutionary trees from other tree-shaped representations that are easily misunderstood as visualising evolutionary relationships. We end by making recommendations for how our findings may be implemented in teaching practice in this important area of biology education.     

Indirect Genetic Effects and the Dynamics of Social Interactions

BackgroundIndirect genetic effects (IGEs) occur when genes expressed in one individual alter the expression of traits in social partners. Previous studies focused on the evolutionary consequences and evolutionary dynamics of IGEs, using equilibrium solutions to predict phenotypes in subsequent generations. However, whether or not such steady states may be reached may depend on the dynamics of interactions themselves.ResultsIn our study, we focus on the dynamics of social interactions and indirect genetic effects and investigate how they modify phenotypes over time. Unlike previous IGE studies, we do not analyse evolutionary dynamics; rather we consider within-individual phenotypic changes, also referred to as phenotypic plasticity. We analyse iterative interactions, when individuals interact in a series of discontinuous events, and investigate the stability of steady state solutions and the dependence on model parameters, such as population size, strength, and the nature of interactions. We show that for interactions where a feedback loop occurs, the possible parameter space of interaction strength is fairly limited, affecting the evolutionary consequences of IGEs. We discuss the implications of our results for current IGE model predictions and their limitations.     

From Mexico to Michigan and back: An international collaboration investigating primate behavior,ecology, and evolution from multiple perspectives

Evolutionary research benefits form the integration of laboratory and field components to determine factors and processes that affect the evolutionary trajectories of species. Our shared interest in understanding hybridization with genetic admixture as a process that may impact social, behavioral, and ecological features of primates, brought us together in a collaborative project aimed at addressing how vocal variation in two species of howler monkeys in Mexico affects and is affected by hybridization. To achieve this goal, we joined our academic expertise in studying primate genetics, ecology, and behavior under different natural and experimental conditions. We took advantage of decades of experience studying and handing wild howler monkeys for translocation projects to safely sample and study wild populations for this project. Here, we describe the history of our collaboration highlighting how our different perspectives, academic realities, and individual strengths built the foundation for our successful collaboration. We also share our perspectives on how this collaboration opened up new academic venues, broadened our individual perspectives on the integration of different research approaches to address a complex topic, and allowed us to recognize the strength of international collaboration.     

Does High-Dose Antimicrobial Chemotherapy Prevent the Evolution of Resistance?

High-dose chemotherapy has long been advocated as a means of controlling drug resistance in infectious diseases but recent empirical studies have begun to challenge this view. We develop a very general framework for modeling and understanding resistance emergence based on principles from evolutionary biology. We use this framework to show how high-dose chemotherapy engenders opposing evolutionary processes involving the mutational input of resistant strains and their release from ecological competition. Whether such therapy provides the best approach for controlling resistance therefore depends on the relative strengths of these processes. These opposing processes typically lead to a unimodal relationship between drug pressure and resistance emergence. As a result, the optimal drug dose lies at either end of the therapeutic window of clinically acceptable concentrations. We illustrate our findings with a simple model that shows how a seemingly minor change in parameter values can alter the outcome from one where high-dose chemotherapy is optimal to one where using the smallest clinically effective dose is best. A review of the available empirical evidence provides broad support for these general conclusions. Our analysis opens up treatment options not currently considered as resistance management strategies, and it also simplifies the experiments required to determine the drug doses which best retard resistance emergence in patients.     

Seasonal consistency of the assembling rules in a bird-fruiting plant network

There is an ongoing debate on whether species' traits or neutrality generate recurrent patterns of mutualistic networks. Although there have been recent advances on the issue, many studies neglect the seasonal dynamics of these drivers. In this study, we investigated how pervasive are the drivers (i.e. species’ size, phenological overlap and species relative abundance) of the frequency of pairwise interactions and the aggregate metrics of seasonal seed dispersal networks in a semideciduous forest from the savannahs of Southeastern Brazil. We used a likelihood approach and built probability matrices based on different drivers to compare how they fit in the frequency and structure of the seasonal observed networks. We found that in both seasons trait-based processes, especially phenological overlap between species, best predicted the frequency of pairwise interactions. However, species relative abundances performed better than species traits in explaining most of aggregate network metrics in both seasons, except for the interaction evenness. These findings suggest that ecological and evolutionary processes are seasonally pervasive and determine the ability of species to interact with their partners. Besides, the general structure of the seasonal networks is less sensitive to species traits and its drivers remain seasonally constant. We conclude that our ability to understand the complexity of plant-frugivore interactions depends on assessing the contribution of species traits and their relative abundances to the structure of seasonal-detailed networks.     

The evolutionary ecology of the Lygaeidae

The Lygaeidae (sensu lato) are a highly successful family of true bugs found worldwide, yet many aspects of their ecology and evolution remain obscure or unknown. While a few species have attracted considerable attention as model species for the study of insect physiology, it is only relatively recently that biologists have begun to explore aspects of their behavior, life history evolution, and patterns of intra‐ and interspecific ecological interactions across more species. As a result though, a range of new phenotypes and opportunities for addressing current questions in evolutionary ecology has been uncovered. For example, researchers have revealed hitherto unexpectedly rich patterns of bacterial symbiosis, begun to explore the evolutionary function of the family's complex genitalia, and also found evidence of parthenogenesis. Here we review our current understanding of the biology and ecology of the group as a whole, focusing on several of the best‐studied characteristics of the group, including aposematism (i.e., the evolution of warning coloration), chemical communication, sexual selection (especially, postcopulatory sexual selection), sexual conflict, and patterns of host‐endosymbiont coevolution. Importantly, many of these aspects of lygaeid biology are likely to interact, offering new avenues for research, for instance into how the evolution of aposematism influences sexual selection. With the growing availability of genomic tools for previously “non‐model” organisms, combined with the relative ease of keeping many of the polyphagous species in the laboratory, we argue that these bugs offer many opportunities for behavioral and evolutionary ecologists.     

Invasibility as an emergent property of native metapopulation structure

Biological invasions constitute major threats to global biodiversity. Eco‐evolutionary considerations highlight the importance of contemporary evolution in community responses to bioinvasions. However, effects of metapopulation structure on invasion success have been mostly overlooked even though metapopulation structure determines gene flow and is likely to affect evolutionary processes. Here, we investigate a stepping‐stone model with evolving alien native interaction strengths. We demonstrate analytically that the site of invasion can determine the success of an invading consumer because gene flow and demography of a local resource species interact to obstruct local resource adaptation. Our main results are 1) that invasion success is more likely in genetic sink populations of the native species and 2) that invasion is more likely to occur against the migrational flow of native species. These findings suggest that invasibility is best regarded as an emergent property not only of communities but of entire metapopulations. Since migration networks of aliens and natives are often mismatched due to anthropogenic interference, our results indicate how population structure eases the spread of invasives against the migrational flow of natives.     

Gill surface area provides a clue for the respiratory basis of brain size in the blacktip shark (Carcharhinus limbatus)

Brain size varies dramatically, both within and across species, and this variation is often believed to be the result of trade-offs between the cognitive benefits of having a large brain for a given body size and the energetic cost of sustaining neural tissue. One potential consequence of having a large brain is that organisms must also meet the associated high energetic demands. Thus, a key question is whether metabolic rate correlates with brain size. However, using metabolic rate to measure energetic demand yields a relatively instantaneous and dynamic measure of energy turnover, which is incompatible with the longer evolutionary timescale of changes in brain size within and across species. Morphological traits associated with oxygen consumption, specifically gill surface area, have been shown to be correlates of oxygen demand and energy use, and thus may serve as integrated correlates of these processes, allowing us to assess whether evolutionary changes in brain size correlate with changes in longer-term oxygen demand and energy use. We tested how brain size relates to gill surface area in the blacktip shark Carcharhinus limbatus. First, we examined whether the allometric slope of brain mass (i.e., the rate that brain mass changes with body mass) is lower than the allometric slope of gill surface area across ontogeny. Second, we tested whether gill surface area explains variation in brain mass, after accounting for the effects of body mass on brain mass. We found that brain mass and gill surface area both had positive allometric slopes, with larger individuals having both larger brains and larger gill surface areas compared to smaller individuals. However, the allometric slope of brain mass was lower than the allometric slope of gill surface area, consistent with our prediction that the allometric slope of gill surface area could pose an upper limit to the allometric slope of brain mass. Finally, after accounting for body mass, individuals with larger brains tended to have larger gill surface areas. Together, our results provide clues as to how fishes may evolve and maintain large brains despite their high energetic cost, suggesting that C. limbatus individuals with a large gill surface area for their body mass may be able to support a higher energetic turnover, and, in turn, a larger brain for their body mass.     

Eco‐evolution on the edge during climate change

We urgently need to predict species responses to climate change to minimize future biodiversity loss and ensure we do not waste limited resources on ineffective conservation strategies. Currently, most predictions of species responses to climate change ignore the potential for evolution. However, evolution can alter species ecological responses, and different aspects of evolution and ecology can interact to produce complex eco‐evolutionary dynamics under climate change. Here we review how evolution could alter ecological responses to climate change on species warm and cool range margins, where evolution could be especially important. We discuss different aspects of evolution in isolation, and then synthesize results to consider how multiple evolutionary processes might interact and affect conservation strategies. On species cool range margins, the evolution of dispersal could increase range expansion rates and allow species to adapt to novel conditions in their new range. However, low genetic variation and genetic drift in small range‐front populations could also slow or halt range expansions. Together, these eco‐evolutionary effects could cause a three‐step, stop‐and‐go expansion pattern for many species. On warm range margins, isolation among populations could maintain high genetic variation that facilitates evolution to novel climates and allows species to persist longer than expected without evolution. This ‘evolutionary extinction debt’ could then prevent other species from shifting their ranges. However, as climate change increases isolation among populations, increasing dispersal mortality could select for decreased dispersal and cause rapid range contractions. Some of these eco‐evolutionary dynamics could explain why many species are not responding to climate change as predicted. We conclude by suggesting that resurveying historical studies that measured trait frequencies, the strength of selection, or heritabilities could be an efficient way to increase our eco‐evolutionary knowledge in climate change biology.     

The evolution of coexistence: Reciprocal adaptation promotes the assembly of a simple community

Species coexistence may result by chance when co‐occurring species do not strongly interact or it may be an evolutionary outcome of strongly interacting species adapting to each other. Although patterns like character displacement indicate that coexistence has often been an evolutionary outcome, it is unclear how often the evolution of coexistence represents adaptation in only one species or reciprocal adaptation among all interacting species. Here, we demonstrate a strong role for evolution in the coexistence of guppies and killifish in Trinidadian streams. We experimentally recreated the temporal stages in the invasion and establishment of guppies into communities that previously contained only killifish. We combined demographic responses of guppies and killifish with a size‐based integral projection model to calculate the fitness of the phenotypes of each species in each of the stages of community assembly. We show that guppies from locally adapted populations that are sympatric with killifish have higher fitness when paired with killifish than guppies from allopatric populations. This elevated fitness involves effects traceable to both guppy and killifish evolution. We discuss the implications of our results to the study of species coexistence and how it may be mediated through eco‐evolutionary feedbacks.     

Feather function and the evolution of birds

The ability of feathers to perform many functions either simultaneously or at different times throughout the year or life of a bird is integral to the evolutionary history of birds. Many studies focus on single functions of feathers, but any given feather performs many functions over its lifetime. These functions necessarily interact with each other throughout the evolution and development of birds, so our knowledge of avian evolution is incomplete without understanding the multifunctionality of feathers, and how different functions may act synergistically or antagonistically during natural selection. Here, we review how feather functions interact with avian evolution, with a focus on recent technological and discovery-based advances. By synthesising research into feather functions over hierarchical scales (pattern, arrangement, macrostructure, microstructure, nanostructure, molecules), we aim to provide a broad context for how the adaptability and multifunctionality of feathers have allowed birds to diversify into an astounding array of environments and life-history strategies. We suggest that future research into avian evolution involving feather function should consider multiple aspects of a feather, including multiple functions, seasonal wear and renewal, and ecological or mechanical interactions. With this more holistic view, processes such as the evolution of avian coloration and flight can be understood in a broader and more nuanced context.     

Habitat geometry, population viscosity and the rate of genetic drift

In all natural populations, individuals located close to one another tend to interact more than those further apart. The extent of population viscosity can have important implications for ecological and evolutionary processes. Here we develop a spatially explicit population model to examine how the rate of genetic drift depends upon both spatial population structure and habitat geometry. The results show that the time to fixation for a new and selectively neutral mutation is dramatically increased in viscous populations. Furthermore, in viscous populations the time to fixation depends critically on habitat geometry. Fixation time for populations of identical size increases markedly as landscape width decreases and length increases. We suggest that similar effects will also be important in metapopulations, with the spatial arrangement of subpopulations and their connectivity likely to determine the rate of drift. We argue that the recent increases in computer power should facilitate major advances in our understanding of evolutionary landscape ecology over the next few years, and suggest that the time is ripe for a unification of spatial population dynamics theory, landscape ecology and population genetics.     

Integrating across life-history stages: consequences of natal habitat effects on dispersal

Ecological and evolutionary processes are affected by forces acting at both local and regional scales, yet our understanding of how these scales interact has remained limited. These processes are fundamentally linked through individuals that develop as juveniles in one environment and then either remain in the natal habitat or disperse to new environments. Empirical studies in a diverse range of organisms have demonstrated that the conditions experienced in the natal habitat can have profound effects on the adult phenotype. This environmentally induced phenotypic variation can in turn affect the probability that an individual will disperse to a new environment and the ecological and evolutionary impact of that individual in the new environment. We synthesize the literature on this process and propose a framework for exploring the linkage between local developmental environment and dispersal. We then discuss the ecological and evolutionary implications of dispersal asymmetries generated by the effects of natal habitat conditions on individual phenotypes. Our review indicates that the influence of natal habitat conditions on adult phenotypes may be a highly general mechanism affecting the flow of individuals between populations. The wealth of information already gathered on how local conditions affect adult phenotype can and should be integrated into the study of dispersal as a critical force in ecology and evolution.     

Matchmaking, metrics and money: a pathway to progress in translational research

In the 24 years since the founding of BioEssays, the level of translational research, as well as the expectations for its success, have burgeoned. Based on our analysis of current and projected US efforts to establish effective centers of translational research, our own institutional experience and discussions with academic research center leaders and institutional research executives, we have arrived at several critical conclusions about how best to foster disease-based research on the institutional, national and international level, what summary statistics may best serve as a measurement of successful practice, roughly how much more money will be required to fund the ongoing venture in the US and how to organize and promote this vision.     

Genetic correlations and the coevolutionary dynamics of three-species systems

The majority of species interact with at least several others. We develop simple genetic models of coevolution between three species where interactions are mediated by quantitative traits. We assume that one of the species has two quantitative traits, each of which governs its interaction with one of the other two species. We use this model to explore how genetic correlations between the two traits in the multivariate species shape the evolutionary dynamics and outcomes of three species interactions. Our results suggest that genetic correlations are most important when at least one of the interactions is between a predator and prey or parasite and host. In these cases, genetic correlations between traits lead to a wide variety of novel coevolutionary outcomes and dynamics. In particular, genetic correlations can affect the existence and stability of coevolutionary equilibrium points, and they can lead to recurrent or permanent maladaptation. When the three species interact only as competitors or mutualists, however, genetic correlations have no effect on the outcome of coevolution. In all cases, our results reveal the surprising conclusion that both positive and negative genetic correlations between traits have qualitatively identical effects on coevolutionary dynamics.     

The associations between social-media use and academic performance among undergraduate students in biology

Recent studies have been conducted in regards to the use of social- media by students and how it can impact his/her academic performance. However, much of this research has been focused on how to use social-media websites in the classroom to facilitate student learning. Therefore, we aimed to address how the use of social-media can be either beneficial or detrimental to undergraduate students, with respect to their academic performance. We distributed a survey to 234 participants, all attending the same four-year university. Throughout the survey, the students self-reported their grade point average (GPA), study habits, and social-media use. We established that female students use social-media websites more often than their male peers, and using a Pearson’s correlation, we found that GPA negatively correlated with the number of social-media websites to which students subscribe (p < 0.05). Furthermore, we found that using more social-media websites correlated positively with the amount of time students spend using social-media platforms on a daily basis. Although previous studies indicate that social-media websites should be incorporated into the classroom, our results suggest that this addition may have negative effects on the study habits and academic performance of undergraduate students, particularly those within the field of biological sciences.     

Stabilizing selection and adaptive evolution in a combination of two traits in an arctic ungulate

Stabilizing selection is thought to be common in wild populations and act as one of the main evolutionary mechanisms, which constrain phenotypic variation. When multiple traits interact to create a combined phenotype, correlational selection may be an important process driving adaptive evolution. Here, we report on phenotypic selection and evolutionary changes in two natal traits in a semidomestic population of reindeer (Rangifer tarandus) in northern Finland. The population has been closely monitored since 1969, and detailed data have been collected on individuals since they were born. Over the length of the study period (1969–2015), we found directional and stabilizing selection toward a combination of earlier birth date and heavier birth mass with an intermediate optimum along the major axis of the selection surface. In addition, we demonstrate significant changes in mean traits toward earlier birth date and heavier birth mass, with corresponding genetic changes in breeding values during the study period. Our results demonstrate evolutionary changes in a combination of two traits, which agree closely with estimated patterns of phenotypic selection. Knowledge of the selective surface for combinations of genetically correlated traits are vital to predict how population mean phenotypes and fitness are affected when environments change.