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.     

Phylogeny and species traits predict bird detectability

Avian acoustic communication has resulted from evolutionary pressures and ecological constraints. We therefore expect that auditory detectability in birds might be predictable by species traits and phylogenetic relatedness. We evaluated the relationship between phylogeny, species traits, and field‐based estimates of the two processes that determine species detectability (singing rate and detection distance) for 141 bird species breeding in boreal North America. We used phylogenetic mixed models and cross‐validation to compare the relative merits of using trait data only, phylogeny only, or the combination of both to predict detectability. We found a strong phylogenetic signal in both singing rates and detection distances; however the strength of phylogenetic effects was less than expected under Brownian motion evolution. The evolution of behavioural traits that determine singing rates was found to be more labile, leaving more room for species to evolve independently, whereas detection distance was mostly determined by anatomy (i.e. body size) and thus the laws of physics. Our findings can help in disentangling how complex ecological and evolutionary mechanisms have shaped different aspects of detectability in boreal birds. Such information can greatly inform single‐ and multi‐species models but more work is required to better understand how to best correct possible biases in phylogenetic diversity and other community metrics.     

Road-Based Surveys for Estimating Wild Turkey Density in the Texas Rolling Plains

Abstract: Line-transect-based distance sampling has been used to estimate density of several wild bird species including wild turkeys (Meleagris gallopavo). We used inflatable turkey decoys during autumn (Aug-Nov) and winter (Dec-Mar) 2003-2005 at study sites in the Texas Rolling Plains, USA, to simulate Rio Grande wild turkey (M. g. intermedia) flocks. We evaluated detectability of flocks using logistic regression models. Our modeling effort suggested that distance to a flock and flock size played important roles in flock detectability. We also conducted surveys from roads for wild turkeys during November 2004-January 2006. The detection probability of decoy flocks was similar to wild turkey flocks during winter (decoy flock, 69.3 ± 6.2% [x̄ ± 95% CI]; wild turkey flock, 62.2 ± 18.3%) and autumn (decoy flock, 44.1 ± 5.1%; wild turkey flock, 44.7 ± 25.6%), which suggested that using decoys was appropriate for evaluating detectability of wild turkey flocks from roads. We conducted computer simulations to evaluate the performance of line-transect-based distance sampling and examined the power to detect trends in population change. Simulations suggested that population density may be underestimated by 12% during inter and 29% during autumn. Such bias occurred because of incomplete detectability of flocks near roads. Winter surveys tended to have less bias, lower relative variability, and greater power than did autumn surveys. During winter surveys, power was sufficient (≥0.80) to detect a 10-25% change in population density in 8-12 years using ≥100 16-km transects or ≥80 32-km transects. We concluded line-transect-based distance sampling from roads is an efficient, effective, and inexpensive technique for monitoring Rio Grande wild turkey populations across large scales.     

Does accounting for imperfect detection improve species distribution models?

Models of species distributions are increasingly being used to address a variety of problems in conservation biology. In many applications, perfect or constant detectability of species, given presence, is assumed. While this problem has been acknowledged and addressed through the development of occupancy models, we still know little regarding whether addressing the potential for imperfect detection improves the predictive performance of species distribution models in nature. Here, we contrast logistic regression models of species occurrence that do not correct for detectability to hierarchical occupancy models that explicitly estimate and adjust for detectability, and maximum entropy models that attempt to circumvent the detectability problem by using data from known presence locations only. We use a large‐scale, long‐term monitoring database across western Montana and northern Idaho to contrast these models for nine landbird species that cover a broad spectrum in detectability. Overall, occupancy models were similar to or better than other approaches in terms of predictive accuracy, as measured by the Area Under the ROC Curve (AUC) and Kappa, with maximum entropy tending to provide the lowest predictive accuracy. Models varied in the types of errors associated with predictions, such that some model approaches may be preferred over others in certain situations. As expected, predictive performance varied across a gradient in species detectability, with logistic regression providing lower relative performance for less detectable species and Maxent providing lower performance for highly detectable species. We conclude by discussing the advantages and limitations to each approach for developing large‐scale species distribution models.     

Seven polymorphic microsatellite loci for paternity assessment in the mallard (Anas platyrhynchos)

We describe seven polymorphic microsatellite loci for the mallard (Anas platyrhynchos). The microsatellites presented here are highly polymorphic, with on average 12 alleles in a sample of 15 presumably unrelated individuals. Therefore, they enable detailed parentage analysis in wild mallard populations, and can be used to answer many intriguing questions in behavioural ecology and evolutionary biology.     

CHANCE,PURPOSE, AND PROGRESS IN EVOLUTION AND CHRISTIANITY

Evolutionary biology has a complex relationship with ideas of chance, purpose, and progress. Probability plays a subtle role; strikingly, founding figures in statistics were motivated by evolutionary questions. The findings of evolutionary biology have been used both in support of narratives of progress, and in their deconstruction. Likewise, professional biologists bring to their scientific work a set of preconceptions about chance and progress, grounded in their philosophical, religious, and/or political views. From the religious side, questions of purpose are ever‐present. We explore this interplay in five broad categories: chance, progress, intelligence, eugenics, and the evolution of religious practices, each the subject of a semester long symposium. The intellectual influence of evolutionary biology has had a broad societal impact in these areas. Based on our experience, we draw attention to a number of relevant facts that, while accepted by experts in their respective fields, may be unfamiliar outside them. We list common areas of miscommunication, including specific examples and discussing causes: sometimes semantics and sometimes more substantive knowledge barriers. We also make recommendations for those attempting similar dialogue.     

Fitness Landscape Analysis of a tRNA Gene Reveals that the Wild Type Allele is Sub-optimal,Yet Mutationally Robust

Fitness landscape mapping and the prediction of evolutionary trajectories on these landscapes are major tasks in evolutionary biology research. Evolutionary dynamics is tightly linked to the landscape topography, but this relation is not straightforward. Here, we analyze a fitness landscape of a yeast tRNA gene, previously measured under four different conditions. We find that the wild type allele is sub-optimal, and 8–10% of its variants are fitter. We rule out the possibilities that the wild type is fittest on average on these four conditions or located on a local fitness maximum. Notwithstanding, we cannot exclude the possibility that the wild type might be fittest in some of the many conditions in the complex ecology that yeast lives at. Instead, we find that the wild type is mutationally robust (“flat”), while more fit variants are typically mutationally fragile. Similar observations of mutational robustness or flatness have been so far made in very few cases, predominantly in viral genomes.     

More on how and why: cause and effect in biology revisited

In 1961, Ernst Mayr published a highly influential article on the nature of causation in biology, in which he distinguished between proximate and ultimate causes. Mayr argued that proximate causes (e.g. physiological factors) and ultimate causes (e.g. natural selection) addressed distinct ‘how’ and ‘why’ questions and were not competing alternatives. That distinction retains explanatory value today. However, the adoption of Mayr’s heuristic led to the widespread belief that ontogenetic processes are irrelevant to evolutionary questions, a belief that has (1) hindered progress within evolutionary biology, (2) forged divisions between evolutionary biology and adjacent disciplines and (3) obstructed several contemporary debates in biology. Here we expand on our earlier (Laland et al. in Science 334:1512–1516, 2011) argument that Mayr’s dichotomous formulation has now run its useful course, and that evolutionary biology would be better served by a concept of reciprocal causation, in which causation is perceived to cycle through biological systems recursively. We further suggest that a newer evolutionary synthesis is unlikely to emerge without this change in thinking about causation.     

Learning the local landscape of protein structures with convolutional neural networks

One fundamental problem of protein biochemistry is to predict protein structure from amino acid sequence. The inverse problem, predicting either entire sequences or individual mutations that are consistent with a given protein structure, has received much less attention even though it has important applications in both protein engineering and evolutionary biology. Here, we ask whether 3D convolutional neural networks (3D CNNs) can learn the local fitness landscape of protein structure to reliably predict either the wild-type amino acid or the consensus in a multiple sequence alignment from the local structural context surrounding site of interest. We find that the network can predict wild type with good accuracy, and that network confidence is a reliable measure of whether a given prediction is likely going to be correct or not. Predictions of consensus are less accurate and are primarily driven by whether or not the consensus matches the wild type. Our work suggests that high-confidence mis-predictions of the wild type may identify sites that are primed for mutation and likely targets for protein engineering.

     

Maladaptation and natural selection

The transformations George Williams initiated in evolutionary biology seem so blindingly obvious in retrospect that they spur the question of why he saw what no one else did. While most humans are prone to see only what theory predicts, Williams sees in bold relief whatever does not fit. Not an adaptationist or an anti-adaptationist, Williams is better described as a maladaptionist. The challenge of finding evolutionary explanations for apparent maladaptations has been overlooked with casualness akin to that once typical for group selection. Suboptimal traits tend to be dismissed as illustrations of the weakness and stochastic nature of selection compared with mutation and drift. A closer look suggests that such constraints are only one of six possible kinds of explanations for apparently suboptimal designs: mismatch, coevolution, tradeoffs, constraints, reproductive advantage at the expense of the individual, and defenses that are aversive but useful Medicine has asked proximate questions at every possible level but has only begun to ask evolutionary questions about why bodies are vulnerable to disease. Considering all six possible evolutionary reasons for apparently suboptimal traits will spur progress not only in medicine but also more generally in biology. 'Williams Vision" may not yield a net benefit to the possessor, but it is invaluable for the species.     

Lessons from EEO: Toward a Universal Evolutionary Curriculum

We propose a human-centered evolutionary curriculum based around the three questions: Who am I? Where do I come from? How do I fit in? We base our curriculum on our experiences as an evolutionary biologist/paleontologist (NE) and as a secondary level special education science teacher (GE)—and not least from our joint experience as co-editors-in-chief of this journal. Our proposed curriculum starts and ends with human biology and evolution, linking these themes with topics as diverse as the “tree of life” (systematics), anthropology, Charles Darwin, cultural evolution, ecology, developmental biology, molecular evolution/genetics, paleontology, and plate tectonics. The curriculum is “universal” as it is designed to be taught at all levels, K–16. The curriculum is flexible: “modules” may be expanded and contracted, reordered, or modified to fit specific grade level needs—and the requirements and interests of local curricula and teachers. We further propose that students utilize workbooks from online or printed sources to investigate the local answers to the general questions (e.g., “Who am I?”), while classroom instruction is focused on the larger scale issues outlined in the modules of our curriculum.     

Evolutionary theory and the foundation of moral principles

Evolutionary biology is supposed to be relevant to ethics by a number of authors. Some of them believe that it may provide and justify basic moral values. Others argue that evolutionary biology is relevant only in a negative way. They assume that it reveals the illusory nature of any attempt to justify basic moral values. In this paper one example of either approach is criticized. An analysis of examples can hardly offer sufficient grounds for a general conclusion. Nevertheless I believe that evolutionary theory is of little help when we deal with the most basic ethical questions. Three themes which are often though to provide a link between evolutionary biology and (meta)ethics — altruism, sociality and human nature — do not in fact establish that link.     

Estimating individual fitness in the wild using capture–recapture data

The concept of Darwinian fitness is central in evolutionary ecology, and its estimation has motivated the development of several approaches. However, measuring individual fitness remains challenging in empirical case studies in the wild. Measuring fitness requires a continuous monitoring of individuals from birth to death, which is very difficult to get in part because individuals may or may not be controlled at each reproductive event and recovered at death. Imperfect detection hampers keeping track of mortality and reproductive events over the whole lifetime of individuals. We propose a new statistical approach to estimate individual fitness while accounting for imperfect detection. Based on hidden process modelling of longitudinal data on marked animals, we show that standard metrics to quantify fitness, namely lifetime reproductive success, individual growth rate and lifetime individual contribution to population growth, can be extended to cope with imperfect detection inherent to most monitoring programs in the wild. We illustrate our approach using data collected on individual roe deer in an intensively monitored population.     

The naturalist in a world of genomics

Functional genomics provides new opportunities to address issues of fundamental interest in evolutionary biology and suggests many new research directions that are ripe for evolutionary investigation. New types of data, and the ability to study biological processes from a whole genome perspective, are likely to have a profound impact on evolutionary biology and ecology. To illustrate, we discuss how genomewide gene expression studies can be used to reformulate questions about trade-offs and pleiotropy. We then touch on some of the new research opportunities that the application of functional genomics affords to evolutionary biologists. We end with some brief notes about how evolutionary biology and comparative approaches will probably have an impact on functional genomics.     

Introduction. Evolutionary dynamics of wild populations: the use of long-term pedigree data

Studies of populations in the wild can provide unique insights into the forces driving evolutionary dynamics. This themed issue of Proc. R. Soc. B focuses on new developments in long-term analyses of animal populations where pedigree information has been collected. These address fundamental questions in evolutionary biology concerning the genetic basis of phenotypic diversity, patterns of natural and sexual selection, the occurrence of inbreeding and inbreeding depression, and speciation. Contributions include the analysis of evolutionary responses to climate change, exploration of the genetic basis of senescence, the exploitation of advances in molecular genetic technology, and reviews of developments in quantitative genetic methodology. We discuss here common themes, specific problems and pointers for future research.     

Developing the genotype-to-phenotype relationship in evolutionary theory: A primer of developmental features

For decades, there have been repeated calls for more integration across evolutionary and developmental biology. However, critiques in the literature and recent funding initiatives suggest this integration remains incomplete. We suggest one way forward is to consider how we elaborate the most basic concept of development, the relationship between genotype and phenotype, in traditional models of evolutionary processes. For some questions, when more complex features of development are accounted for, predictions of evolutionary processes shift. We present a primer on concepts of development to clarify confusion in the literature and fuel new questions and approaches. The basic features of development involve expanding a base model of genotype-to-phenotype to include the genome, space, and time. A layer of complexity is added by incorporating developmental systems, including signal-response systems and networks of interactions. The developmental emergence of function, which captures developmental feedbacks and phenotypic performance, offers further model elaborations that explicitly link fitness with developmental systems. Finally, developmental features such as plasticity and developmental niche construction conceptualize the link between a developing phenotype and the external environment, allowing for a fuller inclusion of ecology in evolutionary models. Incorporating aspects of developmental complexity into evolutionary models also accommodates a more pluralistic focus on the causal importance of developmental systems, individual organisms, or agents in generating evolutionary patterns. Thus, by laying out existing concepts of development, and considering how they are used across different fields, we can gain clarity in existing debates around the extended evolutionary synthesis and pursue new directions in evolutionary developmental biology. Finally, we consider how nesting developmental features in traditional models of evolution can highlight areas of evolutionary biology that need more theoretical attention.     

Evolutionary Novelty and the Evo-Devo Synthesis: Field Notes

Accounting for the evolutionary origins of morphological novelty is one of the core challenges of contemporary evolutionary biology. A successful explanatory framework requires the integration of different biological disciplines, but the relationships between developmental biology and standard evolutionary biology remain contested. There is also disagreement about how to define the concept of evolutionary novelty. These issues were the subjects of a workshop held in November 2009 at the University of Alberta. We report on the discussion and results of this workshop, addressing questions about (i) how to define evolutionary novelty and understand its significance, (ii) how to interpret evolutionary developmental biology as a synthesis and its relation to neo-Darwinian evolutionary theory, and (iii) how to integrate disparate biological approaches in general.     

Phylogenetics and the future of helminth systematics

Phylogenetic systematics is a relatively new formal technique that increases the precision with which one can make direct estimates of the history of phylogenetic descent. These estimates are made in the form of phylogenetic trees, or cladograms. Cladograms may be converted directly into classifications or they may be used to test various hypotheses about the evolutionary process. More than 20 phylogenetic analyses of helminth groups have been published already, and these have been used to investigate evolutionary questions in developmental biology, biogeography, speciation, coevolution, and evolutionary ecology.     

Cross-Species Pathogen Transmission and Disease Emergence in Primates

Many of the most virulent emerging infectious diseases in humans, e.g., AIDS and Ebola, are zoonotic, having shifted from wildlife populations. Critical questions for predicting disease emergence are: (1) what determines when and where a disease will first cross from one species to another, and (2) which factors facilitate emergence after a successful host shift. In wild primates, infectious diseases most often are shared between species that are closely related and inhabit the same geographic region. Therefore, humans may be most vulnerable to diseases from the great apes, which include chimpanzees and gorillas, because these species represent our closest relatives. Geographic overlap may provide the opportunity for cross-species transmission, but successful infection and establishment will be determined by the biology of both the host and pathogen. We extrapolate the evolutionary relationship between pathogen sharing and divergence time between primate species to generate “hotspot” maps, highlighting regions where the risk of disease transfer between wild primates and from wild primates to humans is greatest. We find that central Africa and Amazonia are hotspots for cross-species transmission events between wild primates, due to a high diversity of closely related primate species. Hotspots of host shifts to humans will be most likely in the forests of central and west Africa, where humans come into frequent contact with their wild primate relatives. These areas also are likely to sustain a novel epidemic due to their rapidly growing human populations, close proximity to apes, and population centers with high density and contact rates among individuals.     

Hierarchical phylogenetics as a quantitative analytical framework for evolutionary developmental biology

Phylogenetics has inherent utility in evolutionary developmental biology (EDB) as it is an established methodology for estimating evolutionary relationships and for making comparisons between levels of biological organization. However, explicit phylogenetic methods generally have been limited to two levels of organization in EDB-the species and the gene. We demonstrate that phylogenetic methods can be applied broadly to other organizational levels, such as morphological structures or cell types, to identify evolutionary patterns. We present examples at and between different hierarchical levels of organization to address questions central to EDB. We argue that this application of "hierarchical phylogenetics" can be a unifying analytical approach to the field of EDB.