Evolutionary arguments against moral realism: Why the empirical details matter (and which ones do)

The aim of this article is to identify the strongest evolutionary debunking argument (EDA) against moral realism and to assess on which empirical assumptions it relies. In the recent metaethical literature, several authors have de-emphasized the evolutionary component of EDAs against moral realism: presumably, the success or failure of these arguments is largely orthogonal to empirical issues. I argue that this claim is mistaken. First, I point out that Sharon Street’s and Michael Ruse’s EDAs both involve substantive claims about the evolution of our moral judgments. Next, I argue that combining their respective evolutionary claims can help debunkers to make the best empirical case against moral realism. Some realists have argued that the very attempt to explain the contents of our endorsed moral judgments in evolutionary terms is misguided, and have sought to escape EDAs by denying their evolutionary premise. But realists who pursue this reply can still be challenged on empirical grounds: debunkers may argue that the best, scientifically informed historical explanations of our moral endorsements do not involve an appeal to mind-independent truths. I conclude, therefore, that the empirical considerations relevant for the strongest empirically driven argument against moral realism go beyond the strictly evolutionary realm; debunkers are best advised to draw upon other sources of genealogical knowledge as well.     

Evolutionary Psychology: The Burdens of Proof

I discuss two types of evidential problems with the most widely touted experiments in evolutionary psychology, those performed by Leda Cosmides and interpreted by Cosmides and John Tooby. First, and despite Cosmides and Tooby's claims to the contrary, these experiments don't fulfil the standards of evidence of evolutionary biology. Second Cosmides and Tooby claim to have performed a crucial experiment, and to have eliminated rival approaches. Though they claim that their results are consistent with their theory but contradictory to the leading non-evolutionary alternative, Pragmatic Reasoning Schemas theory, I argue that this claim is unsupported. In addition, some of Cosmides and Tooby's interpretations arise from misguided and simplistic understandings of evolutionary biology. While I endorse the incorporation of evolutionary approaches into psychology, I reject the claims of Cosmides and Tooby that a modular approach is the only one supported by evolutionary biology. Lewontin's critical examinations of the applications of adaptationist thinking provide a background of evidentiary standards against which to view the currently fashionable claims of evolutionary psychology.     

Is science metaphysically neutral?

This paper challenges the claim that science is metaphysically neutral upheld by contenders of the separation of peacefully co-existent science and religion and by evolutionary theists. True, naturalistic metaphysical claims can neither be refuted nor proved and are thus distinct from empirical hypotheses. However, metaphysical assumptions not only regulate the theoretical and empirical study of nature, but are increasingly supported by the growing empirical body of science. This historically evolving interaction has contributed to the development of a naturalistic worldview that renounces the necessity of a transcendent god and of purposeful design. The thesis presented here differs not only from the claims of the "separatists" and of evolutionary theists. In pointing to the metaphysical aspects of science, I also criticize the failure of some evolutionary naturalists to distinguish between empirical and metaphysical contentions. Most important, based on the examination of science suggested here, creationists' false accusation that science is only a naturalistic dogma is refuted. Finally, the difficulties involved in the position endorsed here for the public support of evolution are acknowledged, taking into account the high religious profile of the American society and the social and political context in the US and in other countries.     

On Reciprocal Causation in the Evolutionary Process

Recent calls for a revision of standard evolutionary theory (SET) are based partly on arguments about the reciprocal causation. Reciprocal causation means that cause–effect relationships are bi-directional, as a cause could later become an effect and vice versa. Such dynamic cause-effect relationships raise questions about the distinction between proximate and ultimate causes, as originally formulated by Ernst Mayr. They have also motivated some biologists and philosophers to argue for an Extended Evolutionary Synthesis (EES). The EES will supposedly expand the scope of the Modern Synthesis (MS) and SET, which has been characterized as gene-centred, relying primarily on natural selection and largely neglecting reciprocal causation. Here, I critically examine these claims, with a special focus on the last conjecture. I conclude that reciprocal causation has long been recognized as important by naturalists, ecologists and evolutionary biologists working in the in the MS tradition, although it it could be explored even further. Numerous empirical examples of reciprocal causation in the form of positive and negative feedback are now well known from both natural and laboratory systems. Reciprocal causation have also been explicitly incorporated in mathematical models of coevolutionary arms races, frequency-dependent selection, eco-evolutionary dynamics and sexual selection. Such dynamic feedback were already recognized by Richard Levins and Richard Lewontin in their bok The Dialectical Biologist. Reciprocal causation and dynamic feedback might also be one of the few contributions of dialectical thinking and Marxist philosophy in evolutionary theory. I discuss some promising empirical and analytical tools to study reciprocal causation and the implications for the EES. Finally, I briefly discuss how quantitative genetics can be adapated to studies of reciprocal causation, constructive inheritance and phenotypic plasticity and suggest that the flexibility of this approach might have been underestimated by critics of contemporary evolutionary biology.     

Can You Sequence Ecology? Metagenomics of Adaptive Diversification

Few areas of science have benefited more from the expansion in sequencing capability than the study of microbial communities. Can sequence data, besides providing hypotheses of the functions the members possess, detect the evolutionary and ecological processes that are occurring? For example, can we determine if a species is adapting to one niche, or if it is diversifying into multiple specialists that inhabit distinct niches? Fortunately, adaptation of populations in the laboratory can serve as a model to test our ability to make such inferences about evolution and ecology from sequencing. Even adaptation to a single niche can give rise to complex temporal dynamics due to the transient presence of multiple competing lineages. If there are multiple niches, this complexity is augmented by segmentation of the population into multiple specialists that can each continue to evolve within their own niche. For a known example of parallel diversification that occurred in the laboratory, sequencing data gave surprisingly few obvious, unambiguous signs of the ecological complexity present. Whereas experimental systems are open to direct experimentation to test hypotheses of selection or ecological interaction, the difficulty in “seeing ecology” from sequencing for even such a simple system suggests translation to communities like the human microbiome will be quite challenging. This will require both improved empirical methods to enhance the depth and time resolution for the relevant polymorphisms and novel statistical approaches to rigorously examine time-series data for signs of various evolutionary and ecological phenomena within and between species.     

Ecology, sexual selection and speciation

The spectacular diversity in sexually selected traits among animal taxa has inspired the hypothesis that divergent sexual selection can drive speciation. Unfortunately, speciation biologists often consider sexual selection in isolation from natural selection, even though sexually selected traits evolve in an ecological context: both preferences and traits are often subject to natural selection. Conversely, while behavioural ecologists may address ecological effects on sexual communication, they rarely measure the consequences for population divergence. Herein, we review the empirical literature addressing the mechanisms by which natural selection and sexual selection can interact during speciation. We find that convincing evidence for any of these scenarios is thin. However, the available data strongly support various diversifying effects that emerge from interactions between sexual selection and environmental heterogeneity. We suggest that evaluating the evolutionary consequences of these effects requires a better integration of behavioural, ecological and evolutionary research.     

A new bayesian method for fitting evolutionary models to comparative data with intraspecific variation

Phylogenetic comparative methods that incorporate intraspecific variability are relatively new and, so far, not especially widely used in empirical studies. In the present short article we will describe a new Bayesian method for fitting evolutionary models to comparative data that incorporates intraspecific variability. This method differs from an existing likelihood-based approach in that it requires no a priori inference about species means and variances; rather it takes phenotypic values from individuals and a phylogenetic tree as input, and then samples species means and variances, along with the parameters of the evolutionary model, from their joint posterior probability distribution. One of the most novel and intriguing attributes of this approach is that jointly sampling the species means with the evolutionary model parameters means that the model and tree can influence our estimates of species mean trait values, not just the reverse. In the present implementation, we first apply this method to the most widely used evolutionary model for continuously valued phenotypic trait data (Brownian motion). However, the general approach has broad applicability, which we illustrate by also fitting the λ model, another simple model for quantitative trait evolution on a phylogeny. We test our approach via simulation and by analyzing two empirical datasets obtained from the literature. Finally, we have implemented the methods described herein in a new function for the R statistical computing environment, and this function will be distributed as part of the 'phytools' R library.     

Phylodynamic Inference and Model Assessment with Approximate Bayesian Computation: Influenza as a Case Study

A key priority in infectious disease research is to understand the ecological and evolutionary drivers of viral diseases from data on disease incidence as well as viral genetic and antigenic variation. We propose using a simulation-based, Bayesian method known as Approximate Bayesian Computation (ABC) to fit and assess phylodynamic models that simulate pathogen evolution and ecology against summaries of these data. We illustrate the versatility of the method by analyzing two spatial models describing the phylodynamics of interpandemic human influenza virus subtype A(H3N2). The first model captures antigenic drift phenomenologically with continuously waning immunity, and the second epochal evolution model describes the replacement of major, relatively long-lived antigenic clusters. Combining features of long-term surveillance data from the Netherlands with features of influenza A (H3N2) hemagglutinin gene sequences sampled in northern Europe, key phylodynamic parameters can be estimated with ABC. Goodness-of-fit analyses reveal that the irregularity in interannual incidence and H3N2''s ladder-like hemagglutinin phylogeny are quantitatively only reproduced under the epochal evolution model within a spatial context. However, the concomitant incidence dynamics result in a very large reproductive number and are not consistent with empirical estimates of H3N2''s population level attack rate. These results demonstrate that the interactions between the evolutionary and ecological processes impose multiple quantitative constraints on the phylodynamic trajectories of influenza A(H3N2), so that sequence and surveillance data can be used synergistically. ABC, one of several data synthesis approaches, can easily interface a broad class of phylodynamic models with various types of data but requires careful calibration of the summaries and tolerance parameters.     

Mammals evolve faster on smaller islands

Island mammals often display remarkable evolutionary changes in size and morphology. Both theory and empirical data support the hypothesis that island mammals evolve at faster rates than their mainland congeners. It is also often assumed that the island effect is stronger and that evolution is faster on the smallest islands. I used a dataset assembled from the literature to test these assumptions for the first time. I show that mammals on smaller islands do indeed evolve more rapidly than mammals on larger islands, and also evolve by a greater amount. These results fit well the theory of an evolutionary burst due to the opening of new ecological opportunities on islands. This evolutionary burst is expected to be the strongest on the smallest islands where the contrast between the island and the mainland environments is the most dramatic.     

Gillespie eco‐evolutionary models (GEMs) reveal the role of heritable trait variation in eco‐evolutionary dynamics

Heritable trait variation is a central and necessary ingredient of evolution. Trait variation also directly affects ecological processes, generating a clear link between evolutionary and ecological dynamics. Despite the changes in variation that occur through selection, drift, mutation, and recombination, current eco‐evolutionary models usually fail to track how variation changes through time. Moreover, eco‐evolutionary models assume fitness functions for each trait and each ecological context, which often do not have empirical validation. We introduce a new type of model, Gillespie eco‐evolutionary models (GEMs), that resolves these concerns by tracking distributions of traits through time as eco‐evolutionary dynamics progress. This is done by allowing change to be driven by the direct fitness consequences of model parameters within the context of the underlying ecological model, without having to assume a particular fitness function. GEMs work by adding a trait distribution component to the standard Gillespie algorithm – an approach that models stochastic systems in nature that are typically approximated through ordinary differential equations. We illustrate GEMs with the Rosenzweig–MacArthur consumer–resource model. We show not only how heritable trait variation fuels trait evolution and influences eco‐evolutionary dynamics, but also how the erosion of variation through time may hinder eco‐evolutionary dynamics in the long run. GEMs can be developed for any parameter in any ordinary differential equation model and, furthermore, can enable modeling of multiple interacting traits at the same time. We expect GEMs will open the door to a new direction in eco‐evolutionary and evolutionary modeling by removing long‐standing modeling barriers, simplifying the link between traits, fitness, and dynamics, and expanding eco‐evolutionary treatment of a greater diversity of ecological interactions. These factors make GEMs much more than a modeling advance, but an important conceptual advance that bridges ecology and evolution through the central concept of heritable trait variation.     

Species Invasion History Influences Community Evolution in a Tri-Trophic Food Web Model

Background

Recent experimental studies have demonstrated the importance of invasion history for evolutionary formation of community. However, only few theoretical studies on community evolution have focused on such views.

Methodology and Principal Findings

We used a tri-trophic food web model to analyze the coevolutionary effects of ecological invasions by a mutant and by a predator and/or resource species of a native consumer species community and found that ecological invasions can lead to various evolutionary histories. The invasion of a predator makes multiple evolutionary community histories possible, and the evolutionary history followed can determine both the invasion success of the predator into the native community and the fate of the community. A slight difference in the timing of an ecological invasion can lead to a greatly different fate. In addition, even greatly different community histories can converge as a result of environmental changes such as a predator trait shift or a productivity change. Furthermore, the changes to the evolutionary history may be irreversible.

Conclusions and Significance

Our modeling results suggest that the timing of ecological invasion of a species into a focal community can largely change the evolutionary consequences of the community. Our approach based on adaptive dynamics will be a useful tool to understand the effect of invasion history on evolutionary formation of community.     

Climate change,phenological shifts,eco-evolutionary responses and population viability: toward a unifying predictive approach

The debate on emission targets of greenhouse gasses designed to limit global climate change has to take into account the ecological consequences. One of the clearest ecological consequences is shifts in phenology. Linking these shifts to changes in population viability under various greenhouse gasses emission scenarios requires a unifying framework. We propose a box-in-a-box modeling approach that couples population models to phenological change. This approach unifies population modeling with both ecological responses to climate change as well as evolutionary processes. We advocate a mechanistic embedded correlative approach, where the link from genes to population is established using a periodic matrix population model. This periodic model has several major advantages: (1) it can include complex seasonal behaviors allowing an easy link with phenological shifts; (2) it provides the structure of the population at each phase, including the distribution of genotypes and phenotypes, allowing a link with evolutionary processes; and (3) it can incorporate the effect of climate at different time periods. We believe that the way climatologists have approached the problem, using atmosphere–ocean coupled circulation models in which components are gradually included and linked to each other, can provide a valuable example to ecologists. We hope that ecologists will take up this challenge and that our preliminary modeling framework will stimulate research toward a unifying predictive model of the ecological consequences of climate change.     

Digging through model complexity: using hierarchical models to uncover evolutionary processes in the wild

The growing interest for studying questions in the wild requires acknowledging that eco-evolutionary processes are complex, hierarchically structured and often partially observed or with measurement error. These issues have long been ignored in evolutionary biology, which might have led to flawed inference when addressing evolutionary questions. Hierarchical modelling (HM) has been proposed as a generic statistical framework to deal with complexity in ecological data and account for uncertainty. However, to date, HM has seldom been used to investigate evolutionary mechanisms possibly underlying observed patterns. Here, we contend the HM approach offers a relevant approach for the study of eco-evolutionary processes in the wild by confronting formal theories to empirical data through proper statistical inference. Studying eco-evolutionary processes requires considering the complete and often complex life histories of organisms. We show how this can be achieved by combining sequentially all life-history components and all available sources of information through HM. We demonstrate how eco-evolutionary processes may be poorly inferred or even missed without using the full potential of HM. As a case study, we use the Atlantic salmon and data on wild marked juveniles. We assess a reaction norm for migration and two potential trade-offs for survival. Overall, HM has a great potential to address evolutionary questions and investigate important processes that could not previously be assessed in laboratory or short time-scale studies.     

Context-Dependent Evolutionary Models for Non-Coding Sequences: An Overview of Several Decades of Research and an Analysis of Laurasiatheria and Primate Evolution

The past decade has seen a growing interest in evolutionary models that relax the assumption of site-independent evolution for non-coding sequences. While phylogenetic inference using such so-called context-dependent models is currently computationally prohibitive, these models have been shown to yield significant increases in model fit compared to site-independent evolutionary models, which remain the most widely used evolutionary models to study substitution patterns and perform phylogenetic inference. Context-dependent models have been shown to be suited to study the spontaneous deamination of cytosine in mammalian sequences. In this paper, I discuss various approaches presented in recent years to model context-dependent evolution. I start with discussing the empirical research and results that have led to the development of these models. To accurately estimate the context-dependent substitution patterns that arise from these models, accurate sampling of substitution histories under such models is required. Further, appropriate model selection techniques to assess model performance has become more important than ever, given the drastic increase in parameters of context-dependent models and the tendency of older model selection techniques to prefer parameter-rich models. I also present new results on two mammalian datasets (Primate and Laurasiatheria data) to shed a light on so-called lineage-dependent context-dependent evolution. I conclude this paper with a discussion on current challenges in the development of context-dependent modeling approaches.     

Evolution in heterogeneous environments and the potential of maintenance of genetic variation in traits of adaptive significance

The maintenance of genetic variation in traits of adaptive significance has been a major dilemma of evolutionary biology. Considering the pattern of increased genetic variation associated with environmental clines and heterogeneous environments, selection in heterogeneous environments has been proposed to facilitate the maintenance of genetic variation. Some models examining whether genetic variation can be maintained, in heterogeneous environments are reviewed. Genetic mechanisms that constrain evolution in quantitative genetic traits indicate that genetic variation can be maintained but when is not clear. Furthermore, no comprehensive models have been developed, likely due to the genetic and environmental complexity of this issue. Therefore, I have suggested two empirical approaches to provide insight for future theoretical and empirical research. Traditional path analysis has been a very powerful approach for understanding phenotypic selection. However, it requires substantial information on the biology of the study system to construct a causal model and alternatives. Exploratory path analysis is a data driven approach that uses the statistical relationships in the data to construct a set of models. For example, it can be used for understanding phenotypic selection in different environments, where there is no prior information to develop path models in the different environments. Data from Brassica rapa grown in different nutrients indicated that selection changed in the different environments. Experimental evolutionary studies will provide direct tests as to when genetic variation is maintained.     

Agency in Reproduction

While niche construction theory and developmental approaches to evolution have brought to the front the active role of organisms as ecological and developmental agents, respectively, the role of agents in reproduction has been widely neglected by organismal perspectives of evolution. This paper addresses this problem by proposing an agential view of reproduction and shows that such a perspective has implications for the explanation of the origin of modes of reproduction, the evolvability of reproductive modes, and the coevolution between reproduction and social behavior. After introducing the two prevalent views of agency in evolutionary biology, namely those of organismal agency and selective agency, I contrast these two perspectives as applied to the evolution of animal reproduction. Taking eutherian pregnancy as a case study, I wonder whether organismal approaches to agency forged in the frame of niche construction and developmental plasticity theories can account for the goal-directed activities involved in reproductive processes. I conclude that the agential role of organisms in reproduction is irreducible to developmental and ecological agency, and that reproductive goals need to be included into our definitions of organismal agency. I then explore the evolutionary consequences of endorsing an agential approach to reproduction, showing how such an approach might illuminate our understanding of the evolutionary origination and developmental evolvability of reproductive modes. Finally, I analyze recent studies on the coevolution between viviparity and social behavior in vertebrates to suggest that an agential notion of reproduction can provide unforeseen links between developmental and ecological agency.     

Ecology,thermodynamics and H.T. Odum's conjectures

The central rôle of energy in all life processes has led to the development of numerous hypotheses, conjectures and theories on the relationships between thermodynamics and ecological processes. In this paper we examine the theoretical and empirical support for these developments, and in particular for the widely published set of thermodynamic conjectures developed by H.T. Odum, in which the maximum power principle is put forward as a generic feature of evolution in ecosystems. Although they are widely used, we argue that many of the ecological studies that have adopted the ideas encapsulated in Odum's work have done so without being aware of some of the fundamental problems underlying this approach. We discuss alternative ways in which a general available-work concept could be constructed for use as a numeraire in an energy-centered ecological theory or paradigm. In so doing, we examine what is meant by material accessibility and energy stocks and flows with respect to traditional food web and food chain theories, and relate these to results from the evolutionary dynamics of ecosystems. We conclude that the various forms and uses of energy bound up in essential ecosystem processes present a formidable obstacle to obtaining an operational definition of a general, aggregated available-work concept, a prerequisite for the systems approach of Odum and others. We also show that the prototypical derivations of the maximum power principle, and its interpretation, are contradicted on many scales both by empirical data and models, thereby invalidating the maximum power principle as a general principle of ecological evolution. The conclusions point to the fundamental problem of trying to describe ecosystems in a framework which has a one-dimensional currency.     

A macroevolutionary explanation for energy equivalence in the scaling of body size and population density

Across a wide array of animal species, mean population densities decline with species body mass such that the rate of energy use of local populations is approximately independent of body size. This "energetic equivalence" is particularly evident when ecological population densities are plotted across several or more orders of magnitude in body mass and is supported by a considerable body of evidence. Nevertheless, interpretation of the data has remained controversial, largely because of the difficulty of explaining the origin and maintenance of such a size-abundance relationship in terms of purely ecological processes. Here I describe results of a simulation model suggesting that an extremely simple mechanism operating over evolutionary time can explain the major features of the empirical data. The model specifies only the size scaling of metabolism and a process where randomly chosen species evolve to take resource energy from other species. This process of energy exchange among particular species is distinct from a random walk of species abundances and creates a situation in which species populations using relatively low amounts of energy at any body size have an elevated extinction risk. Selective extinction of such species rapidly drives size-abundance allometry in faunas toward approximate energetic equivalence and maintains it there.     

Eco-evolutionary dynamics

Evolutionary ecologists and population biologists have recently considered that ecological and evolutionary changes are intimately linked and can occur on the same time-scale. Recent theoretical developments have shown how the feedback between ecological and evolutionary dynamics can be linked, and there are now empirical demonstrations showing that ecological change can lead to rapid evolutionary change. We also have evidence that microevolutionary change can leave an ecological signature. We are at a stage where the integration of ecology and evolution is a necessary step towards major advances in our understanding of the processes that shape and maintain biodiversity. This special feature about ‘eco-evolutionary dynamics’ brings together biologists from empirical and theoretical backgrounds to bridge the gap between ecology and evolution and provide a series of contributions aimed at quantifying the interactions between these fundamental processes.