The study of adaptation to climate change requires that we determine what the process of adaptation would converge to, and how far biological systems are removed from these adapted states at any instance. Adapted states can be polymorphic. The phenotypic variability they contain can be constructed by various processes and be assigned to different variance components such as genetic variation, phenotypic plasticity and other effects. With my collaborators and students, I have contributed to the general understanding of factors that selectively favour one process of trait determination over another in adaptive polymorphisms. Individuals are constructed during embryonic development, but this process encompassing any embryonic trait determination is often not considered in adaptation to ecological challenges and in the generation of variability. With students and collaborators, I have prepared a multi-species system of Austrolebias annual killifish where embryos can diapause in the soil to study adaptation including the adaptation of embryonic development. This study will require a life history model of these fish to generate predictions. We have collected data to parameterize such a model in several related species, of which we predicted the phylogenetic relationships. The challenge now is the construction of the model, and developing the equipment and tools to study selection and adaptation of embryonic development in lab and field conditions. This will be the subject of my research and the projects I will supervise in the coming years.
Embryos of annual killifish diapause in soil egg banks while ponds are dry. Their rates of development and survival in different developmental stages determine the numbers and stages of embryos at rewetting. In the Argentinean pearlfish Austrolebias bellottii, we investigated plasticity for desiccation in such embryonal life history components across phases of mild desiccation and rewetting and also effects of life history on hatching. In comparison with nonannuals, our data suggest that incidences of diapause have become relatively independent of the occurrence of desiccation, as if they have become genetically assimilated. We found limited survival effects of desiccation, limited developmental delays, and an acceleration of development into the prehatching stage. This response can be adaptive when desiccation informs that an opportunity to hatch approaches. Embryos arrest development in the prehatching stage (diapause DIII) or in the dispersed‐cell phase (diapause DI). Parental pair variation in rates of development and survival in the earliest developmental stages affects the fraction of embryos that are in DI at rewetting and the number surviving. Given such effects on life history fitness components, rates during embryonal development seem "visible" to selection and the developmental system can thus adapt when pair variation contains a heritable component. In agreement with expectations for the presence of diversified bet‐hedging, some embryos hatched and others not in over half of the clutches with several developed embryos at the moment of rewetting. Hatching probabilities increased for eggs produced later in the experiment, and they increased when embryos were rewetted a second time after two months. This response is opposite of what is expected when age‐dependent hatching would be adapted to exploit opportunities for completing another generation before the dry season.
Identifying the evolutionary and developmental bases of adaptive phenotypes is of central interest in evolutionary biology. Cichlid fishes have been a useful research model due to their extraordinary phenotypic diversity reflecting adaptations to often very narrow niches. Among them, the scale-eating Perissodus microlepis is considered to be a textbook example for balanced polymorphism: its asymmetric head and handed behavior is thought to be maintained by negative frequency-dependent selection via prey–predator interactions. However, several contradictory findings and open questions have emerged in recent years, challenging our understanding of this model. Here, we review existing evidence for both genetic and non-genetic effects influencing head asymmetry, the association between morphological asymmetry and behavioral laterality, and the identification of signatures of balancing selection. Recent technological and theoretical developments have opened new exciting research avenues that can help identifying the drivers of adaptive traits in P. microlepis and other nonmodel organisms, and we discuss promising directions worth exploring. We highlight the importance of using integrative approaches that analyze genetic, environmental, and epigenetic variation in natural populations to aid a comprehensive understanding of why cichlids are so diverse and how evolution has produced and continues to generate such a vibrant and often complex phenotypic diversity.
Temporal trends (1946–2013) in the species richness of wild bees from the Netherlands are analysed. We apply two methods to estimate richness change which both incorporate models for sampling effects and detection probability. The analysis is repeated for records with specimens deposited in collections, and a subset restricted to spatial grid cells that have been sampled repeatedly across three periods. When fitting non-linear species accumulation curves to species numbers, declines are inferred for bumblebees and at most limited declines for other bees. Capture-recapture analysis applied to species encounter histories infers a constant colonization rate per year and constant (bumblebees) or decreasing (other) local species survival. However, simulations suggest that the method estimates time trends in survival with a negative bias. Species richness trends predicted by the second approach are a 10% reduction in non- Bombus species richness and 29% fewer Bombus species since 1946, comparable to the predictions of the first approach. Neither analysis provides reliable evidence that decelerating declines in species richness occur in these taxa. Therefore we should not infer decelerating declines in pollinator species richness in N-W Europe as previously claimed.
Evolutionary innovation contributes to the spectacular diversity of species and phenotypes across the tree of life. ‘Key innovations’ are widely operationalized within evolutionary biology as traits that facilitate increased diversification rates, such that lineages bearing the traits ultimately contain more species than closely related lineages lacking the focal trait. In this article, I briefly review the inference, analysis and interpretation of evolutionary innovation on phylogenetic trees. I argue that differential rates of lineage diversification should not be used as the basis for key innovation tests, despite the statistical tractability of such approaches. Under traditional interpretations of the macroevolutionary ‘adaptive zone’, we should not necessarily expect key innovations to confer faster diversification rates upon lineages that possess them relative to their extant sister clades. I suggest that a key innovation is a trait that allows a lineage to interact with the environment in a fundamentally different way and which, as a result, increases the total diversification—but not necessarily the diversification rate—of the parent clade. Considered alone, branching patterns in phylogenetic trees are poorly suited to the inference of evolutionary innovation due to their inherently low information content with respect to the processes that produce them. However, phylogenies may be important for identifying transformational shifts in ecological and morphological space that are characteristic of innovation at the macroevolutionary scale.
This article is part of the themed issue ‘Process and pattern in innovations from cells to societies’.
In the mid-2000s, molecular phylogenetics turned into phylogenomics, a development that improved the resolution of phylogenetic trees through a dramatic reduction in stochastic error. While some then predicted “the end of incongruence”, it soon appeared that analysing large amounts of sequence data without an adequate model of sequence evolution amplifies systematic error and leads to phylogenetic artefacts. With the increasing flood of (sometimes low-quality) genomic data resulting from the rise of high-throughput sequencing, a new type of error has emerged. Termed here “data errors”, it lumps together several kinds of issues affecting the construction of phylogenomic supermatrices (e.g., sequencing and annotation errors, contaminant sequences). While easy to deal with at a single-gene scale, such errors become very difficult to avoid at the genomic scale, both because hand curating thousands of sequences is prohibitively time-consuming and because the suitable automated bioinformatics tools are still in their infancy. In this paper, we first review the pitfalls affecting the construction of supermatrices and the strategies to limit their adverse effects on phylogenomic inference. Then, after discussing the relative non-issue of missing data in supermatrices, we briefly present the approaches commonly used to reduce systematic error.
With advances in sequencing technologies, there are now massive amounts of genomic data from across all life, leading to the possibility that a robust Tree of Life can be constructed. However, "gene tree heterogeneity", which is when different genomic regions can evolve differently, is a common phenomenon in multi-locus datasets, and reduces the accuracy of standard methods for species tree estimation that do not take this heterogeneity into account. New methods have been developed for species tree estimation that specifically address gene tree heterogeneity, and that have been proven to converge to the true species tree when the number of loci and number of sites per locus both increase (i.e., the methods are said to be "statistically consistent"). Yet, little is known about the biologically realistic condition where the number of sites per locus is bounded. We show that when the sequence length of each locus is bounded (by any arbitrarily chosen value), the most common approaches to species tree estimation that take heterogeneity into account (i.e., traditional fully partitioned concatenated maximum likelihood and newer approaches, called summary methods, that estimate the species tree by combining gene trees) are not statistically consistent, even when the heterogeneity is extremely constrained. The main challenge is the presence of conditions such as long branch attraction that create biased tree estimation when the number of sites is restricted. Hence, our study uncovers a fundamental challenge to species tree estimation using both traditional and new methods.