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Introduction, the language of neo-darwinism, ‘blueprint’, ‘book of life’, the language of neo-darwinism as a whole, an alternative form of representation, conclusions, acknowledgements, evolution beyond neo-darwinism: a new conceptual framework.

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Denis Noble , Hans H. Hoppeler; Evolution beyond neo-Darwinism: a new conceptual framework. J Exp Biol 1 January 2015; 218 (1): 7–13. doi: https://doi.org/10.1242/jeb.106310

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Experimental results in epigenetics and related fields of biological research show that the Modern Synthesis (neo-Darwinist) theory of evolution requires either extension or replacement. This article examines the conceptual framework of neo-Darwinism, including the concepts of ‘gene’, ‘selfish’, ‘code’, ‘program’, ‘blueprint’, ‘book of life’, ‘replicator’ and ‘vehicle’. This form of representation is a barrier to extending or replacing existing theory as it confuses conceptual and empirical matters. These need to be clearly distinguished. In the case of the central concept of ‘gene’, the definition has moved all the way from describing a necessary cause (defined in terms of the inheritable phenotype itself) to an empirically testable hypothesis (in terms of causation by DNA sequences). Neo-Darwinism also privileges ‘genes’ in causation, whereas in multi-way networks of interactions there can be no privileged cause. An alternative conceptual framework is proposed that avoids these problems, and which is more favourable to an integrated systems view of evolution.

This paper represents the culmination of ideas previously developed in a book, The Music of Life ( Noble, 2006 ), and four related articles ( Noble, 2011b ; Noble, 2012 ; Noble, 2013 ; Noble et al., 2014 ). Those publications raised many questions from readers in response to which the ‘Answers’ pages ( http://musicoflife.co.uk/Answers-menu.html ) of The Music of Life website were drafted. Those pages, in particular the page entitled The language of Neo-Darwinism , were written in preparation for the present article. The ideas have been extensively honed in response to further questions and comments.

The recent explosion of research on epigenetic mechanisms described in this issue and elsewhere (e.g. Noble et al., 2014 ), and most particularly work focused on trans-generational inheritance mediated by those mechanisms (e.g. Danchin et al., 2011 ; Dias and Ressler, 2014 ; Gluckman et al., 2007 ; Klironomos et al., 2013 ; Nelson et al., 2012 ; Nelson and Nadeau, 2010 ; Nelson et al., 2010 ; Rechavi et al., 2011 ; Sela et al., 2014 ), has created the need to either extend or replace the Modern (neo-Darwinist) Synthesis ( Beurton et al., 2008 ; Gissis and Jablonka, 2011 ; Noble et al., 2014 ; Pigliucci and Müller, 2010 ). This paper explains why replacement rather than extension is called for. The reason is that the existence of robust mechanisms of trans-generational inheritance independent of DNA sequences runs strongly counter to the spirit of the Modern Synthesis. In fact, several new features of experimental results on inheritance and mechanisms of evolutionary variation are incompatible with the Modern Synthesis. Fig. 1 illustrates the definitions and relationships between the various features of Darwinism, the Modern Synthesis and a proposed new Integrative Synthesis. The diagram is based on an extension of the diagram used by Pigliucci and Müller ( Pigliucci and Müller, 2010 ) in explaining the idea of an extended Modern Synthesis.

The shift to a new synthesis in evolutionary biology can also be seen to be part of a more general shift of viewpoint within biology towards systems approaches. The reductionist approach (which inspired the Modern Synthesis as a gene-centred theory of evolution) has been very productive, but it needs, and has always needed, to be complemented by an integrative approach, including a new theory of causation in biology ( Noble, 2008 ), which I have called the theory of Biological Relativity ( Noble, 2012 ). The approach to replace the Modern Synthesis could be called the Integrative Synthesis as it would be based on the integration of a variety of mechanisms of evolutionary change that must interact, rather than the single mechanism postulated by the Modern Synthesis ( Noble, 2013 ). We are moving to a much more nuanced multi-mechanism theory of evolution, which, interestingly, is closer to some of Darwin's ideas than to neo-Darwinism. Darwin was not a neo-Darwinist. He recognised other mechanisms in addition to natural selection and these included the inheritance of acquired characteristics.

Many of the problems with the Modern Synthesis in accommodating the new experimental findings have their origin in neo-Darwinist forms of representation rather than in experimental biology itself. These forms of representation have been responsible for, and express, the way in which 20th century biology has most frequently been interpreted. In addition, therefore, to the need to accommodate unanticipated experimental findings, we have to review the way in which we interpret and communicate experimental biology. The language of neo-Darwinism and 20th century biology reflects highly reductionist philosophical and scientific viewpoints, the concepts of which are not required by the scientific discoveries themselves. In fact, it can be shown that, in the case of some of the central concepts of ‘selfish genes’ or ‘genetic program’, no biological experiment could possibly distinguish even between completely opposite conceptual interpretations of the same experimental findings ( Noble, 2006 ; Noble, 2011b ). The concepts therefore form a biased interpretive veneer that can hide those discoveries in a web of interpretation.

I refer to a web of interpretation as it is the whole conceptual scheme of neo-Darwinism that creates the difficulty. Each concept and metaphor reinforces the overall mind-set until it is almost impossible to stand outside it and to appreciate how beguiling it is. As the Modern Synthesis has dominated biological science for over half a century, its viewpoint is now so embedded in the scientific literature, including standard school and university textbooks, that many biological scientists may not recognise its conceptual nature, let alone question incoherences or identify flaws. Many scientists see it as merely a description of what experimental work has shown: the idea in a nutshell is that genes code for proteins that form organisms via a genetic program inherited from preceding generations and which defines and determines the organism and its future offspring. What is wrong with that? This article analyses what I think is wrong or misleading and, above all, it shows that the conceptual scheme is neither required by, nor any longer productive for, the experimental science itself.

Diagram illustrating definitions of Darwinism, Modern Synthesis (neo-Darwinism) and Integrated Synthesis. The diagram is derived from Pigliucci and Müller's ( Pigliucci and Müller, 2010 ) presentation of an Extended Synthesis. All the elements are also present in their diagram. The differences are: (1) the elements that are incompatible with the Modern Synthesis are shown coloured on the right; (2) the reasons for the incompatibility are shown in the three corresponding coloured elements on the left. These three assumptions of the Modern Synthesis lie beyond the range of what needs to extend or replace the Modern Synthesis; (3) in consequence, the Modern Synthesis is shown as an oval extending outside the range of the extended synthesis, which therefore becomes a replacement rather than an extension.

I will analyse the main concepts and the associated metaphors individually, and then show how they link together to form the complete narrative. We can then ask what would be an alternative approach better fitted to what we now know experimentally and to a new more integrated systems view. The terms that require analysis are ‘gene’, ‘selfish’, ‘code’, ‘program’, ‘blueprint’ and ‘book of life’. We also need to examine secondary concepts like ‘replicator’ and ‘vehicle’.

Neo-Darwinism is a gene-centred theory of evolution. Yet, its central notion, the ‘gene’, is an unstable concept. Surprising as it may seem, there is no single agreed definition of ‘gene’. Even more seriously, the different definitions have incompatible consequences for the theory.

The word ‘gene’ was introduced by Johannsen ( Johannsen, 1909 ). But the concept had already existed since Mendel's experiments on plant hybrids, published in 1866 (see Druery and Bateson, 1901 ), and was based on ‘the silent assumption [that] was made almost universally that there is a 1:1 relation between genetic factor (gene) and character’ ( Mayr, 1982 ). Of course, no-one now thinks that there is a simple 1:1 relation, but the language of direct causation has been retained. I will call this definition of a ‘gene’ gene J to signify Johannsen's (but essentially also Mendel's) meaning. Since then, the concept of a gene has changed fundamentally. Gene J referred to the cause of a specific inheritable phenotype characteristic (trait), such as eye/hair/skin colour, body shape and mass, number of legs/arms/wings, to which we could perhaps add more complex traits such as intelligence, personality and sexuality.

The molecular biological definition of a gene is very different. Following the discovery that DNA forms templates for proteins, the definition shifted to locatable DNA sequences with identifiable beginnings and endings. Complexity was added through the discovery of regulatory elements (essentially switches), but the basic cause of phenotype characteristics was still thought to be the DNA sequence as that forms the template to determine which protein is made, which in turn interacts with the rest of the organism to produce the phenotype. I will call this definition of a ‘gene’ gene M (see Fig. 2 ).

Relationships between genes, environment and phenotype characters according to current physiological and biochemical understanding. This diagram represents the interaction between DNA sequences, environment and phenotype as occurring through biological networks. The causation occurs in both directions between all three influences on the networks. This view is very different from the idea that genes ‘cause’ the phenotype (right-hand arrow). This diagram also helps to explain the difference between the original concept of a gene as the cause of a particular phenotype (gene J ) and the modern definition as a DNA sequence (gene M ). For further description and analysis see Kohl et al. ( Kohl et al., 2010 ).

But unless all phenotype characteristics are attributable entirely to DNA sequences (which is false: DNA does not act outside the context of a complete cell), gene M cannot be the same as gene J . According to the original view, genes J were necessarily the cause of inheritable phenotypes because that is how they were defined: as whatever in the organism is the cause of that phenotype. Johanssen even left the answer on what a gene might be vague: ‘The gene was something very uncertain, “ein Etwas” [‘anything’], with no connection to the chromosomes’ ( Wanscher, 1975 ). Dawkins ( Dawkins, 1982 ) also uses this ‘catch-all’ definition as ‘an inheritable unit’. It would not matter whether that was DNA or something else or any combination of factors. No experiment could disprove a ‘catch-all’ concept as anything new discovered to be included would also be welcomed as a gene J . The idea becomes unfalsifiable.

The question of causation is now an empirical investigation precisely because the modern definition, genes M , identifies them instead with DNA sequences alone, which omits reference to all other factors. To appreciate the difference, consider Mendel's experiments showing specific phenotypes, such as smooth or wrinkled surfaces of peas. Gene J was whatever in the plant caused the peas to be smooth or wrinkled. It would not make sense to ask whether gene J was the cause. That is how it was defined. It simply is everything that determines the inherited phenotype, i.e. the trait. (Of course, different questions of an empirical nature could be asked about genes J , such as whether they follow Mendel's laws. Some do; some don't.) By contrast, it makes perfect sense to ask whether a specific DNA sequence, gene M , is responsible for determining the phenotype. That question is open to experimental investigation. Gene J could only be the same as gene M if DNA alone determined the phenotype.

This difference between gene J (which refers to indeterminate entities that are necessarily the cause) and gene M (whose causation is open to experimentation) is central and I will use it several times in this article. The difference is in fact large as most changes in DNA do not necessarily cause a change in phenotype. Organisms are very good at buffering themselves against genomic change. Eighty per cent of knockouts in yeast, for example, are normally silent ( Hillenmeyer et al., 2008 ), while critical biological oscillators like the cardiac pacemaker ( Noble, 2011a ) or circadian rhythm ( Foster and Kreitzman, 2004 ) are buffered against genomic change through extensive back-up mechanisms.

The original concept of a gene has therefore been adopted, but then significantly changed by molecular biology. This led to a great clarification of molecular mechanisms, surely one of the greatest triumphs of 20th century biology, and widely acknowledged as such. But the more philosophical consequences of this change for higher level biology are profound and they are much less widely understood. Fig. 2 summarizes the difference.

Some biological scientists have even given up using the word ‘gene’, except in inverted commas. As Beurton et al. ( Beurton et al., 2008 ) comment: ‘It seems that a cell's enzymes are capable of actively manipulating DNA to do this or that. A genome consists largely of semi stable genetic elements that may be rearranged or even moved around in the genome thus modifying the information content of DNA.’ This view is greatly reinforced by the fact that gene expression is stochastic ( Chang et al., 2008 ) and that this itself opens the way to an extensive two-way interaction between the organism's functional networks and the structure and function of chromatin [e.g. figure 10.5 in Kupiec ( Kupiec, 2014 )].

The reason that the original and the molecular biological definitions have incompatible consequences for neo-Darwinism is that only the molecular biological definition, gene M , could be compatible with a strict separation between the ‘replicator’ and the ‘vehicle’. As illustrated in Fig. 2 , a definition in terms of inheritable phenotypic characteristics (i.e. gene J ) necessarily includes much more than the DNA, so that the distinction between replicator and vehicle is no longer valid ( Noble, 2011b ). Note also that the change in definition of a gene that I am referring to here is more fundamental than some other changes that are required by recent findings in genomics, such as the 80% of ‘non-coding’ DNA that is now known to be transcribed ( The_Encode_Project_Consortium, 2012 ) and which also might be included in the molecular biological definition. Those findings raise an empirical question: are those transcriptions as RNAs functional? That would extend gene M to include these additional functional sequences. The difference I refer to, by contrast, is a conceptual one. The difference between gene J and gene M would still be fundamental because it is the difference between necessary and empirically testable causality, not just an extension of the definition of gene M .

There is no biological experiment that could distinguish between the selfish gene theory and its opposites, such as ‘imprisoned’ or ‘co-operative genes’. This point was conceded long ago by Richard Dawkins in his book The Extended Phenotype : ‘I doubt that there is any experiment that could prove my claim’ ( Dawkins, 1982 ). A more complete dissection of the language and possible empirical interpretations of selfish gene theory can be found in Noble ( Noble, 2011b ).

After the discovery of the double helical structure of DNA, it was found that each sequence of three bases in DNA or RNA corresponds to a single amino acid in a protein sequence. These triplet patterns are formed from any combination of the four bases U, C, A and G in RNA and T, C, A and G in DNA. They are often described as the genetic ‘code’, but it is important to understand that this usage of the word ‘code’ carries overtones that can be confusing. This section of the article is not intended to propose that the word ‘code’ should not be used. Its purpose is rather to ensure that we avoid those overtones.

A code was originally an intentional encryption used by humans to communicate. The genetic ‘code’ is not intentional in that sense. The word ‘code’ has unfortunately reinforced the idea that genes are active and even complete causes, in much the same way as a computer is caused to follow the instructions of a computer program. The more neutral word ‘template’ would be better. Templates are used only when required (activated); they are not themselves active causes. The active causes lie within the cells themselves because they determine the expression patterns for the different cell types and states. These patterns are communicated to the DNA by transcription factors, by methylation patterns and by binding to the tails of histones, all of which influence the pattern and speed of transcription of different parts of the genome. If the word ‘instruction’ is useful at all, it is rather that the cell instructs the genome. As the Nobel-prize winner Barbara McClintock said, the genome is an ‘organ of the cell’, not the other way round ( McClintock, 1984 ).

Representing the direction of causality in biology the wrong way round is confusing and has far-reaching consequences. The causality is circular, acting both ways: passive causality by DNA sequences acting as otherwise inert templates, and active causality by the functional networks of interactions that determine how the genome is activated.

The idea of a ‘genetic program’ was introduced by the French Nobel laureates Jacques Monod and Francois Jacob. They referred specifically to the way in which early electronic computers were programmed by paper or magnetic tapes: ‘The programme is a model borrowed from electronic computers. It equates the genetic material with the magnetic tape of a computer’ ( Jacob, 1982 ). The analogy was that DNA ‘programs’ the cell, tissues and organs of the body just as the code in a computer program causally determines what the computer does. In principle, the code is independent of the machine that implements it, in the sense that the code itself is sufficient to specify what will happen when the instructions are satisfied. If the program specifies a mathematical computation, for example, it would contain a specification of the computation to be performed in the form of complete algorithms. The problem is that no complete algorithms can be found in the DNA sequences. What we find is better characterised as a mixture of templates and switches. The ‘templates’ are the triplet sequences that specify the amino acid sequences or the RNA sequences. The ‘switches’ are the locations on the DNA or histones where transcription factors, methylation and other controlling processes trigger their effects. As a program, this is incomplete.

Where then does the full algorithmic logic of a program lie? Where, for example, do we find the equivalent of ‘IF-THEN-ELSE’ type instructions? The answer is in the cell or organism as a whole, not just in the genome.

Take as an example circadian rhythm. The simplest version of this process depends on a DNA sequence Period used as a template for the production of a protein PER whose concentration then builds up in the cytoplasm. It diffuses through the nuclear membrane and, as the nuclear level increases, it inhibits the transcription of Period ( Foster and Kreitzman, 2004 ). This is a negative feedback loop of the kind that can be represented as implementing a ‘program’ like IF LEVEL X EXCEEDS Y STOP PRODUCING X, BUT IF LEVEL X IS SMALLER THAN Y CONTINUE PRODUCING X. But it is important to note that the implementation of this ‘program’ to produce a 24 h rhythm depends on rates of protein production by ribosomes, the rate of change of concentrations within the cytoplasm, the rate of transport across the nuclear membrane, and interaction with the gene transcription control site (the switch). All of this is necessary to produce a feedback circuit that depends on much more than the genome. It depends also on the intricate cellular, tissue and organ structures that are not specified by DNA sequences, which replicate themselves via self-templating, and which are also essential to inheritance across cell and organism generations.

This is true of all such ‘programs’. To call them ‘genetic programs’ or ‘gene networks’ is to fuel the misconception that all the active causal determination lies in the one-dimensional DNA sequences. It doesn't. It also lies in the three-dimensional static and dynamic structures of the cells, tissues and organs.

The postulate of a ‘genetic program’ led to the idea that an organism is fully defined by its genome, whereas in fact the inheritance of cell structure is equally important. Moreover, this structure is specific to different species. Cross-species clones do not generally work. Moreover, when, very rarely, cross-species clones do work, the outcome is determined by the cytoplasmic structures and expression patterns as well as the DNA ( Sun et al., 2005 ). In this connection it is worth noting that the basic features of structural organisation both of cells and of multicellular organisms must have been determined by physical constraints before the relevant genomic information was developed ( Müller and Newman, 2003 ; Newman et al., 2006 ).

As with ‘code’, the purpose of this section is to warn against simplistic interpretations of the implications of the word ‘program’. In the extended uses to which the word has been put in biology, and in modern computing science where the concept of a distributed program is normal, ‘program’ can be used in many different ways. The point is that such a ‘program’ does not lie in the DNA alone. That is also the reason why the concept of a ‘genetic program’ is not testable. By necessarily including non-DNA elements, there is no way of determining whether a ‘genetic program’ exists. At the limit, when all the relevant components have been added in, the ‘program’ is the same as the function it is supposed to be programming. The concept then becomes redundant [p. 53 of Noble ( Noble, 2006 )]. Enrico Coen ( Coen, 1999 ) put the point beautifully when he wrote: ‘Organisms are not simply manufactured according to a set of instructions. There is no easy way to separate instructions from the process of carrying them out, to distinguish plan from execution.’

‘Blueprint’ is a variation on the idea of a program. The word suffers from a similar problem to the concept of a ‘program’, which is that it can be mistaken to imply that all the information necessary for the construction of an organism lies in the DNA. This is clearly not true. The complete cell is also required, and its complex structures are inherited by self-templating. The ‘blueprint’, therefore, is the cell as a whole. But that destroys the whole idea of the genome being the full specification. It also blurs and largely nullifies the distinction between replicator and vehicle in selfish gene theory.

‘ The activity of genes is affected by many things not explicitly encoded in the genome, such as how the chromosomal material is packaged up and how it is labelled with chemical markers. Even for diseases like diabetes, which have a clear inherited component, the known genes involved seem to account for only a small proportion of the inheritance…the failure to anticipate such complexity in the genome must be blamed partly on the cosy fallacies of genetic research. After Francis Crick and James Watson cracked the riddle of DNA's molecular structure in 1953, geneticists could not resist assuming it was all over bar the shouting. They began to see DNA as the “book of life,” which could be read like an instruction manual. It now seems that the genome might be less like a list of parts and more like the weather system, full of complicated feedbacks and interdependencies. ’ ( Editorial, 2010 )

The ‘book of life’ represents the high watermark of the enthusiasm with which the language of neo-Darwinism was developed. Its failure to deliver the promised advances in healthcare speaks volumes. Of course, there were very good scientific reasons for sequencing whole genomes. The benefits to evolutionary and comparative biology in particular have been immense, and the sequencing of genomes will eventually contribute to healthcare when the sequences can be better understood in the context of other essential aspects of physiological function. But the promise of a peep into the ‘book of life’ leading to a cure for all diseases was a mistake.

All parts of the neo-Darwinist forms of representation encourage the use and acceptance of the other parts. Once one accepts the idea that the DNA and RNA templates form a ‘code’, the idea of the ‘genetic program’ follows naturally. That leads on to statements like ‘they [genes] created us body and mind’ ( Dawkins, 1976 ; Dawkins, 2006 ), which gets causality wrong in two ways. First, it represents genes as active causes, whereas they are passive templates. Second, it ignores the many feedbacks on to the genome that contribute to circular causality, in which causation runs in both directions. Those mistakes lead to the distinction between replicators and vehicles. The problem lies in accepting the first step, the idea that there is a ‘code’ forming a complete program.

The distinction between the replicator and the vehicle can be seen as the culmination of the neo-Darwinist way of thinking. If all the algorithms for the processes of life lie in the genome then the rest of the organism does seem to be a disposable vehicle. Only the genome needs to replicate, leaving any old vehicle to carry it.

The distinction, however, is a linguistic confusion and it is incorrect experimentally ( Noble, 2011b ). The DNA passed on from one generation to the next is based on copies (though not always perfect). The cell that carries the DNA is also a copy (also not always perfect). In order for a cell to give rise to daughter cells, both the DNA and the cell have to be copied. The only difference between copying a cell and copying DNA is that the cell copies itself by growing (copying its own detailed structure gradually, which is an example of self-templating) and then dividing so that each daughter cell has a full complement of the complex cell machinery and its organelles, whereas copying DNA for the purpose of inheritance occurs only when the cell is dividing. Moreover, the complexity of the structure in each case is comparable: ‘It is therefore easy to represent the three-dimensional image structure of a cell as containing as much information as the genome’ ( Noble, 2011a ). Faithful genome replication also depends on the prior ability of the cell to replicate itself because it is the cell that contains the necessary structures and processes to enable errors in DNA replication to be corrected. Self-templating must have been prior to the development of the relevant DNA ( Müller and Newman, 2003 ; Newman et al., 2006 ).

My germ line cells are therefore just as much ‘immortal’ (or not) as their DNA. Moreover, nearly all of my cells and DNA die with me. Those that do survive, which are the germ cells and DNA that help to form the next generation, do not do so separately. DNA does not work without a cell. It is simply an incorrect playing with words to single the DNA out as uniquely immortal.

I was also playing with words when I wrote that ‘DNA alone is inert, dead’ ( Noble, 2011b ). But at least that has a point in actual experiments. DNA alone does nothing. By contrast, cells can continue to function for some time without DNA. Some cells do that naturally, e.g. red blood cells, which live for about 100 days without DNA. Others, such as isolated nerve axons, fibroblasts ( Cox et al., 1976 ; Goldman et al., 1973 ) or any other enucleated cell type, can do so in physiological experiments.

Genes M are best viewed therefore as causes in a passive sense. They do nothing until activated. Active causation lies with proteins, membranes, metabolites, organelles, etc., and the dynamic functional networks they form in interaction with the environment ( Noble, 2008 ).

Notice also that the language as a whole is strongly anthropomorphic. This is strange, given that most neo-Darwinists would surely wish to avoid anthropomorphising scientific discovery.

The alternative form of representation depends on two fundamental concepts. The first one is the distinction between active and passive causes. Genes M are passive causes; they are templates used when the dynamic cell networks activate them. The second concept is that there is no privileged level of causation. In networks, that is necessarily true, and it is the central feature of what I have called the theory of biological relativity, which is formulated in a mathematical context ( Noble, 2012 ).

I will illustrate the second point in a more familiar non-mathematical way. Take some knitting needles and some wool. Knit a rectangle. If you don't knit, just imagine the rectangle. Or use an old knitted scarf. Now pull on one corner of the rectangle while keeping the opposite corner fixed. What happens? The whole network of knitted knots moves. Now reverse the corners and pull on the other corner. Again, the whole network moves, though in a different way. This is a property of networks. Everything ultimately connects to everything else. Any part of the network can be the prime mover, and be the cause of the rest of the network moving and adjusting to the tension. Actually, it would be better still to drop the idea of any specific element as prime mover. It is networks that are dynamically functional.

Now knit a three-dimensional network. Again, imagine it. You probably don't actually know how to knit such a thing. Pulling on any part of the three-dimensional structure will cause all other parts to move (cf. Ingber, 1998 ). It doesn't matter whether you pull on the bottom, the top or the sides. All can be regarded as equivalent. There is no privileged location within the network.

The three-dimensional network recalls Waddington's epigenetic landscape network ( Fig. 3 ) and is quite a good analogy to biological networks as the third dimension can be viewed as representing the multi-scale nature of biological networks. Properties at the scale of cells, tissues and organs influence activities of elements, such as genes and proteins, at the lower scales. This is sometimes called downward causation, to distinguish it from the reductionist interpretation of causation as upward causation ( Ellis et al., 2012 ). ‘Down’ and ‘up’ here are also metaphors and should be treated carefully. The essential point is the more neutral statement: there is no privileged scale of causality, beyond the representation of scales, perhaps. This must be the case in organisms, which work through many forms of circular causality. A more complete analysis of this alternative approach can be found in the article on Biological Relativity ( Noble, 2012 ), from which Fig. 4 is taken. One of the consequences of the relativistic view is that genes M cease to be represented as active causes. Templates are passive causes, used when needed. Active causation resides in the networks, which include many components for which there are no DNA templates. It is the physics and chemistry of those dynamic networks that determine what happens.

In certain respects, my article reflects some of the points made over 30 years ago by Ho and Saunders ( Ho and Saunders, 1979 ), who wrote: ‘The intrinsic dynamical structure of the epigenetic system itself, in its interaction with the environment, is the source of non-random variations which direct evolutionary change, and that a proper study of evolution consists in the working out of the dynamics of the epigenetic system and its response to environmental stimuli as well as the mechanisms whereby novel developmental responses are canalized.’ Their ideas also owe much to those of Conrad Waddington – the term ‘canalised’ is one that he often used.

Conrad Waddington's diagram of the epigenetic landscape. Genes (solid pegs at the bottom) are viewed as parts of complex networks so that many gene products interact between themselves and with the phenotype to produce the phenotypic landscape (top) through which development occurs. Waddington's insight was that new forms could arise through new combinations to produce new landscapes in response to environmental pressure, and that these could then be assimilated into the genome. Waddington was a systems biologist in the full sense of the word. If we had followed his lead many of the more naive 20th century popularisations of genetics and evolutionary biology could have been avoided. Image taken from The Strategy of the Genes ( Waddington, 1957 ). Reprinted (2014) by Routledge Library Editions.

An important linguistic feature of the alternative, relativistic, concepts proposed here is that most or all the anthropomorphic features of the neo-Darwinist language can be eliminated, without contravening a single biological experimental fact. There may be other forms of representation that can achieve the same result. It doesn't really matter which you use. The aim is simply to distance ourselves from the biased conceptual scheme that neo-Darwinism has brought to biology, made more problematic by the fact that it has been presented as literal truth.

The extent to which the language of neo-Darwinism has dominated biological thought for over a century since George Romanes invented the term in a letter to Nature ( Romanes, 1883 ) is remarkable. It is a tribute to the inventiveness and persuasiveness of many biologists and to their ability to communicate the original idea and its subsequent formulation as the Modern Synthesis to a very wide public. The integration of the early discoveries of molecular biology also contributed great momentum, particularly as the Central Dogma of Molecular Biology ( Crick, 1970 ) was perceived (incorrectly as it subsequently turned out) to confirm a central assumption, which was that the genome was isolated from the lifestyle of the organism and its environment.

In retrospect, neo-Darwinism can be seen to have oversimplified biology and over-reached itself in its rhetoric. By so conclusively excluding anything that might be interpreted as Lamarckism, it assumed what couldn't be proved. As John Maynard Smith ( Maynard Smith, 1998 ) admitted: ‘It [Lamarckism] is not so obviously false as is sometimes made out’, a statement that is all the more significant from being made by someone working entirely within the Modern Synthesis framework. His qualification on this statement in 1998 was that he couldn't see what the mechanism(s) might be. We can now do so thanks to some ingenious experimental research in recent years.

Nevertheless, the dogmatism was unnecessary and uncalled for. It damaged the reputation of Lamarck, possibly irretrievably. Lamarck should be recognised by biologists generally as one of the very first to coin and use the term ‘biology’ to distinguish our science, and by evolutionary biologists in particular for championing the transformation of species against some very powerful critics. Darwin praised Lamarck for this achievement: ‘This justly celebrated naturalist…who upholds the doctrine that all species, including man, are descended from other species’ (preface to the 4th edition of The Origin of Species , 1866).

Many models of biological systems consist of differential equations for the kinetics of each component. These equations cannot give a solution (the output) without setting the initial conditions (the state of the components at the time at which the simulation begins) and the boundary conditions. The boundary conditions define what constraints are imposed on the system by its environment and can therefore be considered as a form of contextual causation from a higher scale. This diagram is highly simplified to represent what we actually solve mathematically. In reality, boundary conditions are also involved in determining initial conditions and the output parameters can also influence the boundary conditions, while they in turn are also the initial conditions for a further period of integration of the equations. The arrows are not really unidirectional. The dotted arrows complete the diagram to show that the output contributes to the boundary conditions (although not uniquely), and determines the initial conditions for the next integration step. Legend and diagram are reproduced from Noble ( Noble, 2012 ).

Many others were damaged too, Waddington included. A little more humility in recognising the pitfalls that beset the unwary when they think they can ignore some basic philosophical principles would have been a wiser strategy. The great physicist Poincaré pointed out, in connection with the relativity principle in physics, that the worst philosophical errors are made by those who claim they are not philosophers ( Poincaré, 1902 ; Poincaré, 1968 ). They do so because they don't even recognise the existence of the conceptual holes they fall into. Biology has its own version of those conceptual holes.

I thank Peter Hacker, Michael Joyner, Peter Kohl, Jean-Jacques Kupiec, Gerd Müller, Raymond Noble and Amit Saad for valuable discussions and comments on the paper itself, and the many correspondents who commented or asked further questions on the Answers pages on the Music of Life website ( http://musicoflife.co.uk/Answers-menu.html ). I thank Bryce Bergene, Senior Designer, Mayo Clinic Creative Media, for the design of Fig. 1 . A video version of this figure in relation to the original extended synthesis figure can be viewed online ( supplementary material Movie 1 ).

This research received no specific grant from any funding agency in the public, commercial, or not-for-profit sectors.

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As habitat destruction continues to make waterways murkier, the ability for animals to see in the cloudy water is becoming more important. Tiarks, Gray and Chapman show that young cichlids have larger eyes when raised in murky waters but not larger brains.

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• Published: 04 May 2022

Correcting misconceptions about evolution: an innovative, inquiry-based introductory biological anthropology laboratory course improves understanding of evolution compared to instructor-centered courses

• Susan L. Johnston 1 ,
• Maureen Knabb 1 ,
• Josh R. Auld 1 &
• Loretta Rieser-Danner 1  

Evolution: Education and Outreach volume  15 , Article number:  6 ( 2022 ) Cite this article

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Comprehensive understanding of evolution is essential to full and meaningful engagement with issues facing societies today. Yet this understanding is challenged by lack of acceptance of evolution as well as misconceptions about how evolution works that persist even after student completion of college-level life science courses. Recent research has suggested that active learning strategies, a focus on science as process, and directly addressing misconceptions can improve students’ understanding of evolution. This paper describes an innovative, inquiry-based laboratory curriculum for introductory biological anthropology employing these strategies that was implemented at West Chester University (WCU) in 2013–2016. The key objectives were to help students understand how biological anthropologists think about and explore problems using scientific approaches and to improve student understanding of evolution. Lab activities centered on scenarios that challenged students to solve problems using the scientific method in a process of guided inquiry. Some of these activities involved application of DNA techniques. Formative and summative learning assessments were implemented to measure progress toward the objectives. One of these, a pre- and post-course evolution concepts survey, was administered at WCU (both before and after the implementation of the new curriculum) and at three other universities with more standard introductory biological anthropology curricula. Evolution survey results showed greater improvement in understanding from pre- to post-course scores for WCU students compared with students at the comparison universities (p < .001). WCU students who took the inquiry-based curriculum also had better understanding of evolution at the post-course period than WCU students who took the course prior to implementation of the new curriculum (p < .05). In-class clicker assessments demonstrated improved understanding of evolution concepts (p < .001) and scientific method (p < .05) over the course of individual labs. Two labs that involved applying DNA methods received the highest percentage ratings by students as ‘very useful’ to understanding important concepts of evolution and human variation. WCU student ratings of their confidence in using the scientific method showed greater improvement pre- to post-course during the study period as compared with the earlier, pre-implementation period (p < .05). The student-centered biological anthropology laboratory curriculum developed at WCU is more effective at helping students to understand general and specific concepts about evolution than are more traditional curricula. This appears to be directly related to the inquiry-based approach used in the labs, the emphasis on knowledge and practice of scientific method, directly addressing misconceptions about evolution, and a structure that involves continual reinforcement of correct concepts about evolution and human variation over the semester.

Understanding the reality of evolution is fundamental to science education. However, many Americans deny the theory of evolution despite overwhelming evidence and uniform support from the scientific community (Nadelson and Hardy 2015 ). In 2006, Miller et al. published an enlightening study demonstrating the low acceptance of evolution in the United States compared to 34 other countries, with the US ranking second to last in acceptance of evolution. Data from the Pew Research Center’s ( 2015 ) Religious Landscape Study show that these results had not changed very much in the intervening decade; at that time, 34% of Americans reported that they reject evolution and believe that humans arrived on earth in their present form. Recent work by Miller et al. ( 2021 ) suggests this may be changing, with increased public acceptance of evolution in the last decade. Even though acceptance of evolution increases with level of education, from 20% in high school to 52% and 65% among college or postgraduates, respectively, the rejection rate of evolution from students in introductory biology classes can reach up to 50% (Brumfield 2005 ; Rice et al. 2010 ; Paz-y-Miño-C and Espinosa 2016 ). Even college-level instruction in evolution, then, may not increase students’ acceptance of evolution.

Perhaps more surprisingly, even when acceptance of evolution is not a factor, college-level instruction does not necessarily result in full understanding of evolution either, and numerous studies identify multiple evolution-related misconceptions held by different groups of students. For example, Cunningham and Wescott ( 2009 ) identified and evaluated biological anthropology students’ misconceptions about evolution and found that, despite acceptance of evolutionary theory, students lack understanding of the process of evolution. Tran et al. ( 2014 ) also identified similar misconceptions among advanced undergraduate biology majors. And Beggrow and Sbeglia ( 2019 ) reported that despite some differences in evolutionary reasoning and in the specific types of evolution misconceptions held by biology and anthropology majors, both populations performed poorly on a measure of evolutionary knowledge (Conceptual Inventory of Natural Selection [CINS]; Anderson et al. 2002 ). Several other instruments to assess both student misconceptions about evolution and student understanding of evolution have been developed, including the Measure of the Acceptance of Evolutionary Theory (MATE; Rutledge and Sadler 2007 ) and the Inventory of Students’ Acceptance of Evolution (I-SEA; Nadelson and Southerland 2012 ) with different student populations (see also Nehm and Mead 2019 ; Furrow and Hsu 2019 ). Results of multiple studies using these instruments show that student misconceptions continue despite college-level classroom instruction (e.g., Beggrow and Sbeglia 2019 ). Use of these types of assessment instruments aids in understanding and addressing student misconceptions, but there clearly remains a need to find the most effective teaching and learning strategies for evolution education (Glaze and Goldston 2015 ).

Pobiner ( 2016 ) recently reviewed the current state of evolution teaching and learning and concluded that focusing on human examples, such as in biological anthropology courses, is an effective way to enhance student understanding and acceptance of evolution. Based on results of the "Teaching Evolution through Human Examples" project (Pobiner et al. 2015 , 2018 ), these authors suggest that the use of human examples is helpful because human examples are relevant, they increase students’ acceptance and understanding of evolution, and they help students to appreciate historical science. Numerous other investigators have supported this suggestion (e.g., see Beggrow and Sbeglia 2019 ) and some research suggests that students across multiple disciplines (majors and non-majors) actually prefer the use of human examples when learning about evolution (e.g., Pobiner et al. 2018 ; Paz-y-Miño-C and Espinosa 2016 ). However, even with a focus on human evolution, misconceptions continue to exist (e.g., Cunningham and Westcott 2009 ; Beggrow and Sbeglia 2019 ).

Some research suggests that instructor-centered pedagogy (lecture) is less successful in helping students recognize and correct their misconceptions about evolution (Bishop and Anderson 1990 ; Gregory 2009 ) compared to historically rich, problem-solving methods of instruction that appear to significantly improve student understanding of evolution (Jensen and Finley 1996 ). Nehm and Reilly ( 2007 ) directly compared pedagogical approaches using pre- and post-course tests and found that students taught using active-learning techniques performed better than those using a more traditional approach.

Pittinsky ( 2015 ) further suggests that firsthand experience with scientific methods, as well as interactions with real scientists, would help address some of the problems in teaching evolution. It seems that when students learn to think like a scientist and use the same actions that led to original discoveries, they gain insight into the strategies and techniques used by scientists studying evolution (Passmore and Stewart 2002 ). Scharmann et al. ( 2018 ) and Nelson et al. ( 2019 ) also suggest that Nature of Science (NOS) principles should be covered before even introducing the theory of evolution. Some research supports this suggestion. For example, DeSantis ( 2009 ) reported that introduction of a curriculum module that included inquiry-based activities that model the work of paleontologists increased interest in and acceptance of the theory of evolution among middle- and high-school age students. Might the inclusion of similar inquiry-based laboratory activities also reduce the evolution misconceptions held by students (at all levels)?

Other research suggests that the order in which concepts are introduced makes a difference in students’ understanding of evolution, at least among high school students. For example, Mead et al. ( 2017 ) reported that teaching genetics first (before evolution) improves student understanding of evolution. And, Alters and Nelson ( 2002 ) as well as Beggrow and Sbeglia ( 2019 ) further suggest that targeting naïve ideas about evolution should be an instructional goal, particularly in anthropology education. Research by Bishop and Anderson ( 1990 ) and Jensen and Finley ( 1996 ) support this suggestion, reporting that confronting students’ misconceptions directly before introducing correct conceptions is associated with significant gains in student understanding of evolution. Wingert et al. ( 2022 ) show that employing instructional activities that directly challenge students' teleological concepts about natural selection improves their acceptance and understanding of evolution. 

Taken together, these results support Nelson’s ( 2008 ) recommendation of three learning strategies to improve student understanding of evolution: (1) extensively using active learning strategies; (2) focusing on science as a process and way of knowing; and (3) identifying and directly addressing student misconceptions. We report on the effectiveness of an inquiry-based laboratory curriculum that incorporates all of these strategies in an undergraduate biological anthropology course.

Evolutionary theory is central to the discipline of biological anthropology, which is fundamentally about human evolution. At West Chester University (WCU), Biological Anthropology (ANT 101) is a general education, introductory course taken by majors and non-majors that had, traditionally, been taught using a teacher-centered approach. In 2010, assessment data indicated that many students retained common misconceptions about evolution after completion of the course. For example, responses to the question “What is evolution?” included replies such as: “…survival of the fittest, species do what they need to do to pass their genes on”; “the change that occurs in an environment over time from a change in species”; “the way an organism changes to survive in a changing environment.” Clearly course changes were needed to address these misconceptions, and it seemed a good idea to attempt to do so by actively engaging students in understanding the concepts of evolution as well as the tools used by researchers to solve problems using scientific methods. Based on previous work emphasizing the need to employ human examples using active, hands-on pedagogy that emphasizes the scientific process, we developed an innovative biological anthropology laboratory course that merges these three important components of effective teaching of evolution. Based on our results, this course not only improves overall performance in correcting misconceptions when compared to other biological anthropology courses, but it also significantly improves understanding in specific areas.

Introduction to Biological Anthropology (ANT 101) has been offered annually or more frequently at WCU for nearly two decades. It is a required course for anthropology majors, and for most of that time period non-majors have been permitted to take it to meet a general education distributive requirement. Until the fall semester of 2013, it was configured as a three-hour per week lecture course with no hands-on lab component, and the department had no access to laboratory classroom facilities. For several of those years, the instructor incorporated 3–5 virtual laboratory experiences over the semester using one lecture hour for each. While students said they enjoyed these experiences, assessment data indicated that they still had persistent misconceptions about evolution at course completion.

In fall 2013, a project team at WCU, including the course instructor (a biological anthropologist), a human physiologist experienced in inquiry curricula, an evolutionary biologist, and a psychologist with expertise in assessment and program evaluation were awarded a three-year TUES (Transforming Undergraduate Education in STEM) grant from the National Science Foundation (NSF). The purpose of this award was to develop an innovative, inquiry-based laboratory curriculum targeting student misconceptions about evolution, student ability to use the scientific method, and student understanding of the investigative tools used by biological anthropologists. To accommodate this new curriculum, the course was redesigned to meet four hours per week in an integrated lecture-lab format, with roughly half of that time devoted to laboratory activities and the other half to lecture and/or discussion.

The project was submitted to the West Chester University Human Subjects Committee and received expedited approval in the summer 2013. Informed consent was obtained each semester from students enrolled in the course who wished to participate. Over the period of the project, this was all but one or two students.

During each lab period, brief instruction on methodology was provided, as appropriate to the lab, and students were presented with a challenge scenario that asked them to apply the scientific process to solving that problem using the relevant method (with the challenge scenario providing a structured context in which to do so). In a standard biological anthropology lab curriculum, students might be asked to describe and identify various casts of hominin fossil skulls using characteristics they had learned about, associate these traits with dietary differences, and receive verification of their assessments by the instructor. In the inquiry-based, structured challenge approach developed at WCU, students were given a problem to solve that required them to hypothesize the likely diet of the various hominins or hominids. They were instructed in a technique that allowed them to test one of their hypotheses, then required to state their results in an organized manner, evaluate them, indicate next steps, and so on. Thus, each lab in the curriculum is configured to (1) help students understand how biological anthropologists think about and explore problems using relevant techniques and (2) gain experience with the scientific process. The lab curriculum includes some instruction and application of basic molecular techniques (e.g., constructing simple primate phylogenies based on morphological v. genetic variation and doing a DNA fingerprinting exercise to attempt to identify a hypothetical hominin fossil), since the curriculum is also designed to help students make connections between phenotypic observations and the molecular level in service of the project goal of helping students to better understand evolution. Table 1 provides a list of the labs with descriptions of the inquiry learning activities performed.

The full lab manual can be accessed at: https://digitalcommons.wcupa.edu/anthrosoc_facpub/72 .

Standard assessments, including periodic exams and laboratory reports, were utilized to measure student learning. Responses to lab challenges at multiple time points were evaluated at the end of each semester using a rubric to measure individual students’ abilities to define the problem, to develop a plan to solve the problem, to analyze and present information, and to interpret findings and solve the challenge problem. Student lab teams also developed a project that they designed and implemented (from hypothesis to interpretation) using one of the methods they learned, and gave group presentations to the class. Other, more formative, measures of student learning were also introduced. For example, during each lab, students completed a pre-post assessment tool which was a modified version of the RSQC2 (Recall, Summarize, Question, Connect, and Comment) classroom assessment technique developed by Angelo and Cross ( 1993 ). Beginning in the second year of the project, pre- and post-lab clicker questions were incorporated for rapid assessment of the lab impact.

Several global surveys were administered at the beginning of each course, prior to any instruction, and again (for all but one survey) on the last day of the course. These included a survey focusing on evolution (17 items in year one, revised to 25 items in the second year) as well as surveys assessing students’ familiarity and comfort level with the scientific process, their level of motivation, and, at the end only, their overall assessment of their course experience. The evolution survey was also administered at WCU for 2 years prior to the course reorganization and lab implementation; data from this period are used for an internal comparison with survey results obtained during the implementation of the new curriculum. Biological anthropology colleagues at three other US universities (reported here as A, B, and C) also administered the evolution concepts survey to their students in introductory courses in biological anthropology, during the grant period, for comparison purposes. All of these courses were taught with some version of a more standard laboratory curriculum for this discipline (example of a standard approach described above). University ‘A’ is a large, midwestern state school (approximately 40,000 students); University ‘B’ is a sizable state school located in the south (approximately 30,000 students). University ‘C’ is a large, northeastern state school (approximately 30,000 students). At all three, introductory biological anthropology is taught in large lecture context with smaller recitation sections that meet one hour per week (i.e., two hours lecture, one hour of recitation or lab). At A and C, these recitations were used for weekly laboratory activities throughout the semester; at B, there were seven labs during the semester. Prior to 2013, the course at University A had no lab at all—only lecture.

The current report first describes the results of the evolution concepts instrument administered at the very beginning of the course and at the end of the course at WCU and across universities. Following a presentation of the results regarding changes in misconceptions we turn our attention to an examination of the specific areas of learning that we believe may have contributed to the reduction in misconceptions, including a look at specific assessments of students’ growing understanding of science as a process throughout the course.

Evolution misconceptions

Two versions of the evolution concepts instrument were used, one prior to the start of the grant period and throughout the first year following the grant award and a revised version used beginning in fall 2014. Each version included statements that students responded to on a 5-option Likert-type scale ranging from strongly agree to strongly disagree, or having no opinion. This instrument was based on a published and freely available tool used by other researchers (Cunningham and Wescott 2009 ). For purposes of analysis, each item was agreed by the project team to be either true or false, such that strong agreement with a true statement and strong disagreement with a false statement were considered to be ‘correct’ responses. A scale ranging from + 2 to − 2, including 0 for ‘no opinion’ was constructed, and several variables were computed from these scores, including total score (pre, post), percent of total points earned (pre, post), number of items correct (pre, post), and percent of items correct (pre, post). The use of percent variables was necessitated by a revision of the survey after the first year of curriculum implementation (2013–2014). The initial version of the survey included 24 items, but a qualitative analysis by study consultants resulted in a set of only 17 items deemed usable for the purposes of our study. This initial survey was then revised for use beginning in fall 2014 to include the 17 items kept from the original survey with the addition of 8 new items, resulting in a set of 25 usable items. The 25-question survey can be found in Additional file 1 .

Several questions were addressed using the results of the evolution concepts instrument. First, we compared WCU student survey responses to responses from the three other institutions whose students completed the survey. We asked if student performance on the evolution concepts instrument improved from pre- to post-course for all institutions and whether the amount of improvement varied by institution. Second, we examined WCU student survey responses (both pre and post surveys) over time, asking if student performance on the evolution concepts instrument improved both prior to and during the grant implementation period. Next, we asked whether the degree of improvement changed following implementation of our new inquiry-based curriculum, relative to the academic years prior to implementation of the grant. Finally, in an attempt to understand the specifics of what evolution-related misconceptions might have improved and which did not, we conducted a qualitative analysis of survey items and compared student performance on sets of related items across universities.

WCU course assessments

A variety of measures were used to assess student learning throughout each semester at WCU and to evaluate the effectiveness of particular pedagogical approaches as well as the overall curriculum. Some of these measures were objective and direct measures of student learning. Some were indirect measures, student perceptions of what they learned and/or which laboratory sessions they believed were most helpful in their learning. In this report, we provide results of four of these measures—in-class clicker questions, laboratory challenges, RSQC2 responses, and student confidence ratings—to provide insights about the effectiveness of the curriculum in meeting its primary objectives.

In-class clicker questions

Students were presented with a set of true/false statements or multiple choice questions at the beginning and end of multiple laboratory sessions. Some items were tied directly to misconceptions about evolution, others to students’ understanding of the scientific method, while others were designed to measure more general understanding of the topics covered by the individual laboratory modules. Students responded, via clickers, to these statements presented visually in class. Responses served as an important source of formative assessment but also provided information on the effectiveness of each of the laboratory modules in correcting student misconceptions about evolution and student understanding of the scientific method.

Laboratory challenges

Laboratory modules included “challenge” activities, designed specifically to enable students to apply problem-solving skills within a structured context (Knabb and Misquith 2006 ). In each of these laboratory challenges, students were asked to state research questions or generate hypotheses, collect data, draw conclusions, report/graph their results, and reflect on those results. Each student completed a laboratory worksheet during each lab module and all worksheets were submitted as part of student lab notebooks at the end of each semester. Selected lab worksheets were reviewed by faculty involved with the grant project at the end of each semester using a developmental assessment screening tool developed by all project faculty. This screening tool underwent its own developmental process, resulting in a final tool that included four measures of scientific thinking (i.e., students’ ability to use the scientific method): Defining the Problem, Developing a Plan to Assess the Problem, Analyzing and Presenting Information, and Interpreting Findings and Solving the Problem. Each of these four areas was assessed on a scale of four developmental levels: beginning, developing, appropriately developed, and exemplary. A copy of this scoring rubric can be found in Additional file 2 . Developmental changes in these four areas of scientific thinking were assessed by comparing assigned developmental levels following an early semester laboratory module with assigned developmental levels following a later semester laboratory module.

RSQC2 (Revised)

A modified version of the RSQC2 classroom assessment technique (Angelo and Cross 1993 ) was completed by students during each laboratory session. Complete details about the multiple sections of this activity can be found in Additional file 3 . For the current report, we present data on one of the sections completed by students at the end of each laboratory session. Students were asked to rate the usefulness of each laboratory session in reaching learning outcomes. Ratings were made on a 4-point Likert scale: 4 = very useful; 3 = somewhat useful; 2 = minimally useful; 1 = not useful. Questions included: How useful was today’s laboratory session in helping you to understand the important concepts of evolution and human variation discussed in this course and used by biological anthropologists? How useful was today’s laboratory session in helping you to understand the tools used by biological anthropologists to understand the concepts of evolution and human variation?

Student confidence in using scientific method

WCU students completed a 10-item survey at both the beginning and the end of each semester asking them to rate their level of confidence in their abilities and/or understanding of several pieces of the scientific process. All items were rated on a 5-point Likert scale: 1 = completely doubtful; 2 = somewhat doubtful; 3 = neutral; 4 = somewhat confident; 5 = strongly confident. A copy of this survey is available in Additional file 4 .

A variety of both univariate and multivariate linear model procedures were used to address questions of interest involving all student assessments, both within and across time periods and universities (where appropriate). Specifics regarding these analyses are discussed within the Results section.

Evolution misconceptions at WCU and other institutions

WCU evolution surveys were collected across all six semesters of the grant implementation period (fall 2013 through spring 2016), with a total of 105 complete survey sets (pre- and post-course). Survey responses from students at the three other universities were provided by institution instructors whenever possible: University A provided 469 complete survey sets across five terms; University B provided 273 complete survey sets across six terms; and University C provided 200 complete survey sets across three terms. Comparisons across universities were made across only the three terms for which data was provided by each university (fall 2014, spring 2015, and fall 2015). Figure  1 shows pre-course and post-course percent items correct at each university (WCU, University A, University B, and University C), collapsed across these three semesters.

Pre-course and post-course evolution concept survey ‘percent items answered correctly’ across 4 universities: WCU (n = 43); University A (n = 308); University B (n = 143); and University C (n = 200)

Significant change from pre- to post-course percent items correct was found within institutions for each of the three terms individually [as assessed after each term] and across all terms combined. Furthermore, significant change from pre- to post-course percent items correct was found across all three terms and 4 institutions, collapsed [t (693) = 25.762, p < 0.001]. Thus, significant improvement in overall performance on the evolution misconceptions instrument occurred at every institution and during each of the three terms considered here.

While there were no significant differences by term, institution, or term x institution in pre-course percent items correct, we did note a near significant effect of institution [F (3, 690) = 2.548, p < 0.10]. An informal review revealed that WCU pre-course scores were higher than pre-course percent items correct at all three other universities. Thus, comparison of post-course percent items correct included the pre-course percent items correct scores as a covariate. ANCOVA results support a significant effect of institution on post-course percent items correct, after controlling for pre-course percent items correct [F (3, 689) = 8.345, p < 0.001]. Post-hoc tests show significant differences between post-course scores at WCU and at all three other institutions. In addition, post-course percent items answered correctly at University B was significantly lower than percent items answered correctly at University C.

Internal WCU comparisons

The results reported above support statistically significant improvement in evolution misconception scores among students at all participating universities but further suggest that post-course scores are significantly higher at WCU than at any of the other three universities, even after controlling for potential differences in pre-course scores. WCU differs from these other institutions in terms of the curriculum focus (our inquiry-based approach versus other, more standard approaches), but WCU also differs from the other institutions in terms of class size. Individual class sections are smaller at WCU, resulting in smaller sample sizes both within and across semesters. If class size is the factor that explains the difference in post-course performance across universities, it should also be the case that post-course performance at WCU would not change following the introduction of the new inquiry-based curriculum. To evaluate this possibility, we compared WCU evolution survey results for pre-grant terms to evolution survey results following implementation of the inquiry-based curricular approach. Survey results are reported here for pre-grant (fall 2011 and fall 2012, N = 22 and 26, respectively), and grant implementation (fall 2013, spring 2014, fall 2014, spring 2015, fall 2015, and spring 2016; Ns = 18, 23, 12, 12, 19, and 21, respectively) (Fig.  2 ).

WCU pre- and post-course ‘percent items answered correctly’ by project phase: pre-grant (n = 48) and post-grant (n = 105)

There were no significant differences by term in pre-course percent items correct or post-course percent items correct during the pre-grant period (fall 2011 and fall 2012) or during the grant implementation period (fall 2013 through spring 2016). Significant change from pre- to post-course percent items correct was found across the pre-grant period [t (47) = 7.387, p < 0.001] and across the grant implementation period [t (104) = 14.871, p < 0.001]. Thus, significant improvement in performance on the evolution conceptions instrument was found both prior to and during the implementation of the grant. There were no significant differences in pre-course percent items correct between pre-grant and grant implementation periods [F (1, 151) = 2.145, p = 0.145]. But, a significant group difference was found in post-course percent items correct [F (1,151) = 5.600, p < 0.05], with students answering a larger percentage of items correctly (i.e., earning full 2 points) across the grant implementation period than during the pre-grant period.

Evolution concepts

The results reported above support the conclusion that our new laboratory curriculum may be more effective in improving student understanding of evolution and evolutionary concepts and may be more effective in reducing student misconceptions of evolution than the curriculums utilized at the other universities. In addition, significantly more WCU students answered certain survey items correctly at the post-course assessment than did students at any of the other three institutions (see Table 2 ), but a clear pattern was difficult to identify. Thus, we conducted a qualitative analysis of the 25 survey items that made up the revised version of the survey (the one implemented beginning fall 2014). We examined the survey results for the three terms for which data were available for all four institutions (fall 2014, spring 2015, fall 2015). This analysis resulted in four groups of items, each addressing one broad theme: (1) understanding of basic scientific evidence and the process of science (5 items); (2) understanding of evolution (from a general or “big picture” perspective) (7 items); (3) understanding of the mechanisms of evolution (i.e., natural selection, mutation, genetic drift, gene flow) (8 items); and (4) understanding of the evidence for evolution (5 items). Table 2 provides a list of all survey items and identifies which theme each item falls into.

A significant multivariate effect of institution was found when we included the four concept scores (i.e., percent of items within each concept grouping answered correctly) in a MANOVA procedure with both pre-course scores and post-course scores included as dependent variables. Univariate follow-up tests suggest a significant institution effect for Concepts #1, and #4. In both cases, pre-course scores were higher for WCU students than for students at other institutions. Thus, a set of Analysis of Covariance (ANCOVA) procedures were conducted, one for each set of post-course concept scores (i.e., percent of items within each concept grouping answered correctly at post-course time period), with institution included as a between-subjects factor and pre-course scores for that concept included as a covariate. Results suggest a significant institution effect for three of the four concepts (#1, #2, and #3). With regard to Concept #1 (understanding of basic scientific evidence and the process of science) post-hoc tests following an overall significant effect of institution [F (3,689) = 3.919, p < 0.05] show significantly higher post-course concept scores at WCU than at any of the other three institutions. A similar result was found for Concept #2 (understanding of evolution from a general/big picture perspective) [F (3,689) = 12.899, p < 0.001]. Again, post-course scores for WCU were significantly greater than those for the other three institutions. In addition, University A post-course scores were significantly greater than those for University B. A significant effect of institution was also found for Concept #3 (understanding of the mechanisms of evolution) [F (3,689) = 7.278, p < 0.001]. Post-hoc tests reveal that WCU post-course scores are significantly greater than those of University A and University B. WCU scores are higher than those of University C but that difference did not reach statistical significance. No significant effect of institution was found for Concept #4 scores (understanding of the evidence for evolution) [F (3,689) = 1.643, p = 0.178). But, despite the lack of an overall significant effect, WCU post-course scores are greater than those of the other institutions for this concept. Descriptive statistics for the concept scores across universities can be found in Additional file 5 .

How might this inquiry-based course have aided in the reduction of evolutionary misconceptions? In an attempt to gain insight about which course components or processes were effective in this regard, we examined student responses to in-class clicker questions about evolution concepts and scientific method , their development of scientific thinking skills over the term via lab worksheets, their perceptions about each lab’s effectiveness in helping them to learn about evolution and human variation concepts, and their confidence in using the scientific method. These results are presented below.

Clicker questions were developed over the course of the second year of the grant, then revised slightly for use across the final year of the grant (Fall 2015–Spring 2016). Questions were developed for eleven laboratory modules (see Table 1 ). Some items were included within each module to measure understanding of specific laboratory content. Items measuring evolution misconceptions were also included for all modules (1, 2, or 3 items). Items measuring scientific thinking (i.e., understanding of the scientific method) were included for only three modules (1 or 2 items): Evolution and Scientific Thinking, Primate Anatomy and Locomotion, and Human Osteology and Forensics. Clicker questions were presented at the beginning and at the end of each laboratory module session. Data for the final year of grant implementation are presented here. Complete data (across all laboratory modules) were available for 24 students across both semesters.

Overall student performance (as measured by % total items answered correctly) increased significantly from 78.64% at pre-module assessment to 91.06% at post-module assessment (across all items and all laboratory modules) [t (23) = 10.89, p < 0.001]. Performance also increased within each of the laboratory modules.

Student performance also increased significantly on the items specifically designed to measure previously identified misconceptions about evolution, with percent total items answered correctly across all laboratory modules increasing from 83.85% correct to 91.93% correct (across all items and all laboratory modules) [t (23) = 4.992, p < 0.001]. Given that evolutionary misconceptions were addressed most steadily during the early part of the semester, we examined the degree to which improvement on misconception items might be different across the semester. Table 3 shows measures of student performance on evolution misconception in-class clicker items during three time periods of the semester: Early Semester (3 modules focused on basic evolutionary concepts); Mid Semester (4 modules focused on non-human primates and human evolution); and Late Semester (4 modules focused on living human biology). While some slight improvement was noted across all time periods, the only period during which a statistically significant improvement occurred was the early semester time period.

Student performance on the items specifically designed to measure student understanding of the scientific method increased significantly from 90.00% to 97.50% (across all items and all three laboratory modules that included those items) [t (23) = 2.584, p < 0.05]. When broken down by individual laboratory module, the greatest improvement in student performance appears in the later modules but is only statistically significant in the Primate Locomotion module (see Table 4 ).

Two laboratory sessions (one early- and one mid-semester) were chosen for comparison: (1) the Evolution and Scientific Thinking laboratory module was chosen for the early-semester session; and (2) the Primate Anatomy and Locomotion module was chosen for the mid-semester session. The Evolution and Scientific Thinking laboratory module was the first laboratory module students participated in and occurred during week two of the semester. The Primate Anatomy and Locomotion session occurred at about week six of the semester. Four variables were scored from the laboratory worksheets of each of these sessions across the final two semesters of the grant implementation period, fall 2015–spring 2016: Defining the Problem; Developing a Plan to Solve the Problem; Analyzing and Presenting Information; and Interpreting Findings and Solving the Problem. All were rated on a scale of 1 to 4 (Beginning, Developing, Appropriately Developed, and Exemplary). Three faculty scorers worked together to determine final scores by consensus for each variable in each laboratory worksheet. Complete data were available for a total of 42 students across both semesters (21 each semester) (see Table 5 ).

Student responses to all items of the RSQC2 classroom assessment tool were collected across the final two semesters of the grant implementation period, fall 2015–spring 2016. As outlined earlier, students were asked to rate the usefulness of each laboratory session in helping them to understand (1) the important concepts of evolution and human variation discussed in the course, and (2) the tools used by biological anthropologists to understand the concepts of evolution and human variation. Students ranked each laboratory session, as it ended, on a 4-point scale, ranging from Not Useful to Very Useful, on each of these items. Table 6 lists the laboratory session topics and the percent of students who rated each one as “Very Useful” to their understanding of the important concepts of evolution and human variation. Table 7 lists the percent of students who rated each one as “Very Useful” to their understanding of the tools used by biological anthropologists (i.e., to their understanding of the scientific method as practiced by biological anthropologists). Some differences in student ratings across the two areas of understanding are apparent.

Student ratings of their confidence in using the scientific method are reported here for the pre-grant period (fall 2011 and fall 2012 combined), and the grant implementation period (fall 2013, spring 2014, fall 2014, spring 2015, fall 2015, and spring 2016 combined) (see Table 8 ). Student ratings increased from pre- to post-course during both time periods, but improvement was greater during the grant implementation period than during the pre-grant period.

The laboratory curriculum developed and evaluated at WCU increases students’ understanding of evolution in introductory biological anthropology compared with other institutions using more standard approaches. While students taking the evolution concepts survey demonstrated improved understanding of evolution at all of the schools that employed this instrument (WCU and comparisons) from the beginning to the end of each semester, WCU students demonstrated a greater increase in percent items answered correctly from pre- to post-course (see Fig.  1 ). Significantly more WCU students answered 18 (of 25) survey items correctly at the post-course assessment than did students at any of the other three institutions (see Table 2 ). Given that WCU class sizes are smaller than those at the three comparison universities, WCU student performance on the evolution survey before the new curriculum was implemented was compared with performance during the first three years of the new, grant-funded curriculum. Students taking the survey during the grant period answered a statistically greater percentage of items correct at the post-survey than students in the pre-grant period, with pre-survey response levels showing no significant difference across these two phases (see Fig.  2 ); class sizes were comparable across the entire time frame.

Thus, we demonstrate the impact on improved student understanding of evolution is related to the new curriculum itself. In the remaining discussion, we focus on the question of what aspects of the new curriculum may be contributing to this improvement, detailing how this curriculum incorporates all three of the key learning strategies outlined by Nelson ( 2008 ): (1) extensive use of active learning approaches; (2) focus on science as a process and way of knowing; and (3) identification and direct targeting of student misconceptions.

First, the WCU curriculum is inquiry-based, engaging students actively and directly with the process of “doing science”. Active learning (also known as student-centered learning) strategies, such as problem- or inquiry-based approaches, have been shown to be superior to instructor-centered approaches (e.g., lecture) in promoting student learning about evolution (e.g., Jensen and Finley 1996 ; Nehm and Reilly 2007 ). One of the stated learning goals of this course is to help students come to understand how biological anthropologists investigate questions. We strive to accomplish this by having them learn and actually use some of the tools scientists in this field employ—both at the ‘outward’ physical (e.g., skeletal, body shape and size, etc.) and molecular/biochemical levels (e.g., gene sequence readouts, DNA fingerprinting)—in a problem-solving context. Student lab teams receive a challenge scenario and have to come up with a methodological approach (usually using techniques they have just learned, and occasionally employing techniques learned earlier in the course), collect data, and then interpret those data—in every lab. This is fundamentally different than the typical approach in an introductory biological laboratory setting, such as those used in the comparison institutions and described earlier in this paper.

We think that this bi-level approach to teaching and using relevant methods in problem-solving helps students connect the evidence for evolution and human variation with the underlying molecular basis of that variation and change over time. Student ratings of each lab on the RSQC2 question pertaining to effectiveness in helping them to learn concepts of evolution and human variation were highest for Tree-Building and Primate Classification and DNA Fingerprinting (Table 6 ). We think it telling that both of these labs involve genetic as well as phenotypic variation linked with evolution. Ratings for the question concerning lab effectiveness in helping students to learn to use the tools biological anthropologists employ to understand evolution and human variation were highest for Forensics 2: DNA Fingerprinting, followed by Human Variation: Anthropometry, Human Genetic Adaptation: ELISA, and the Tree-Building and Primate Classification labs (see Table 7 ); all but the anthropometry lab address directly both genetic/biochemical and physical traits.

Second, the WCU curriculum focuses on the scientific way of knowing and the scientific process from the first week, in both lecture and lab contexts. The first topic after the students are introduced to the discipline is the nature of science: how science seeks to understand phenomena, the meaning of ‘fact’, ‘hypothesis’, and ‘theory’ in a scientific inquiry, and how the scientific approach to understanding natural phenomena differs from others. The first lab, which occurs early in the second week, then provides an opportunity for students to try out the scientific method and to learn, in context, about generating hypotheses, developing methods, collecting data, and interpreting those observations. They also learn about bias caused by preconceptions, measurement error, and different approaches to understanding the world (e.g., science and religion). Each lab module thereafter requires students to methodically think through and structure their work using the standard methodological sequence: question/hypothesis, explication of methods, data collection and reporting, discussion, and interpretation (see Table 1 ). Further examples of how the process of science is addressed in the curriculum are described below in the discussion about addressing evolution misconceptions.

The effectiveness of this approach is supported by the qualitative evolution concepts analysis that we undertook to look for thematic patterns in the evolution survey statements (see Table 2 and associated text). Three broad concepts showed a significant effect of institution, with WCU student post-course scores being higher than those at the other institutions; the first of these was understanding of basic scientific evidence and the process of science. The in-class clicker data we analyzed (see Table 4 ) support the idea that students gained knowledge about the scientific method during lab classes. Analysis of the change in student performance on lab challenges relevant to steps of the scientific process from early to mid-semester (see Table 5 ) also supports improved student ability to develop a plan to solve the problem (Methods) and to analyze and present information (Results) from the early time point to the later one. Additionally, students’ report of their confidence in using the scientific method (see Table 8 ) indicated greater improvement from pre- to post-course during the grant implementation period than during the pre-grant period at WCU. Firsthand experience with the scientific method and opportunities to ‘think like a scientist’ have been linked with improved ability of students to understand and accept evolution (see, e.g., Pittinsky 2015 ; DeSantis 2009 ; Robbins and Roy 2007 ; Nelson 2008 ).

Third, the WCU curriculum is designed to identify and directly address student misconceptions about evolution, and it does so from early in the course (Nelson 2008 ). Students take the evolution concepts survey on the first day of class, before any instruction about evolution. This provides a baseline of their understanding, and the concepts included in the survey are among those that the curriculum proceeds to address. The order of the labs over the semester (Table 1 ) ensures that basic concepts of evolutionary theory and mechanisms, genetics, and classification/phylogeny are covered early. As part of this attention to foundational ideas, class discussions during and at the end of labs include a focus on misconceptions about evolution and, indeed, about how scientific inquiry is conducted. For example, in the Evolution and Scientific Thinking lab (the first one), students nearly always assume the male skeleton will be the taller of the two—whether or not they overtly state that as a hypothesis. This and other ideas that students mention lead to a discussion of assumption bias and how we try to avoid that in the process of “doing” science. This is followed by a dialogue (sometimes precipitated by a student-expressed view, but more often introduced by the instructor as a story) focused on the idea some people hold that the male should have one less rib than the female. We talk through whether this is a scientific hypothesis (yes, because it can be tested); how they would test it (go count the ribs); what kind of evolution mechanism this idea reflects (Lamarkism, i.e., inheritance of acquired characteristics); and what genetic assumption is also being made (that rib number is sex-linked). We also tell students that, in reality, there is a range of variation in number of rib pairs in humans. In fact, the male skeleton is shorter than the female, and this fact also fosters a framework in which to look at what kinds of factors may affect variation in height in humans, besides sex (e.g., population or individual ancestry, various environmental influences, age). In the Tree Building and Primate Classification two-part lab, we address directly the relationship among monkeys, apes, and humans. At the outset, most students think that monkeys and apes are more closely related evolutionarily than either group is to humans; this is also typically how they interpret the anatomic evidence of the comparative skulls and build their initial trees. However, when they do the counts of pairwise differences in the gene sequence for the three primate groups, they come to understand that the genetic evidence is indicating that apes and humans are more closely related than either group is to monkeys. The discussion in this lab is also focused on the conduct of science inquiry (e.g., can we say a hypothesis is “proven” based on one gene sequence or a limited set of anatomic traits?) and evolution misconceptions (e.g., that extant species differ from each other in “how evolved” or better adapted they are, based on body size or some other assumption).

In addition, we assess student understanding about common misconceptions in all labs directly via some of the in-class clicker questions administered as a formative assessment at the beginning and end of each lab module. Use of clickers allows us to assess immediately, at the conclusion of a lab module, how well students grasped the key concepts and techniques on which the lab was based, including evolution concepts. In the data presented in this paper, scores on evolution concept clicker questions improved significantly in the early lab modules analyzed as a group compared with mid-semester and later semester groupings of lab modules (see Table 3 ). In the later phases, the baseline (pre-lab) scores were higher, reflecting student mastery of evolution concepts generally over course duration. Finally, evolution misconceptions were also addressed in ‘lecture’ class discussions as well as queried on exams. In other words, the focus on correcting misconceptions occurred at multiple levels and time points in the course.

The kind of repetition and reinforcement that we describe here has been termed “spaced practice” or “varied practice” and is documented as improving student conceptual learning (Brown et al. 2014 ; Cepeda et al. 2006 ; Lang 2016 ). Spaced practice improves learning for a variety of reasons and in a variety of ways, but one thing that spaced practice supports is long-term consolidation of information; practice over time and in various forms allows for the connection of new information to existing knowledge and for the strengthening of memory traces over time (Brown et al. 2014 ; Cepeda et al. 2006 ; Goode et al. 2008 ; Moulton et al. 2006 ). We think that reinforcing on a weekly basis both the scientific method and correct general and specific concepts about evolution (including the mechanisms of evolution) represents this kind of spaced and varied practice and may well be contributing to the comparative success of this curriculum. The close integration of lecture and lab is likely also a factor.

Following the project, the course instructor, in consultation with the project team, made a number of changes to the curriculum based on the promising findings described above. The steps of the scientific method were more explicitly built into all of the lab worksheets, for emphasis. Opportunities to emphasize key evolution concepts within particular labs were enhanced during post-lab discussions. Clicker questions were revised to incorporate more statements reflecting science process and understanding, as well as additional repetitions of evolution concepts (with altered wording each time). Eventually, two new labs were developed related to human physiological adaptability. The first of these was added in spring of 2017 and focused on blood pressure response to stress; this lab, done late in the semester, then became the basis for the students’ final group project (instead of the population ancestry lab). After the students conduct a pro-forma experiment assessing cardiovascular response to a stressor using the blood pressure sensor and software, they design and conduct their own experiments, which they then present orally the following week. In fall 2017, a second physiology lab was added in the first half of the course, focused on skin temperature response to cold, and provided another, and earlier, opportunity for students to develop their own experiments once they learned the technique, with an emphasis at this early stage on hypothesizing. Students present these first ‘mini’ projects briefly (focusing on hypothesis and results) the following week. We felt that it was important to provide students with two experiences that allow them to ask and answer research questions of their own, under guidance. In fall 2017 the course topic order was also altered, bringing most of the human biology material previously covered at the end (biological variability and adaptation) into the sequence immediately after evolutionary theory and genetics—thus the relevance of a temperature adaptability lab in week 5.

Conclusions and suggestions

The student-centered biological anthropology laboratory curriculum developed at WCU is more effective at helping students to understand general and specific concepts about evolution than are more traditional curricula. We argue here that this is not just a function of small class size, but is directly related to the inquiry-based approach used in the labs, the emphasis on knowledge of science and practice applying the scientific method regularly, the very intentional confronting of misconceptions about evolution starting early in the course, and the structure that allows for ‘spaced practice’, i.e., continual reinforcement of correct concepts about evolution and human variation. Inquiry-based approaches can be incorporated in lab sections of otherwise large lecture courses (Casotti et al. 2008 ) or as small-group activities within lecture-only science courses. Evidence suggests that these student-centered approaches also work well for diverse learners (Tuan et al. 2005 ).

We encourage instructors of introductory biological anthropology and other life science courses to incorporate these key elements in their curricula to support improved student understanding about science process and evolution. Three general suggestions that might be applied fairly readily based on our study would be: (1) assess students’ level of understanding of evolution and how science proceeds right at the beginning of the course or relevant unit, and again at the end—to take stock of the impact of the curriculum on student learning; (2) provide hands-on problem-solving opportunities, such as case studies, guided challenges, or self-designed experiments, that iteratively emphasize scientific method and correct understanding of evolution; (3) use human examples where possible, and look for opportunities to help students connect the phenotypic changes reflecting evolution with the underlying genetic changes. The WCU curriculum is freely available to those who are interested in more detail or who may wish to adapt and incorporate components of what we have discussed here in their own courses—e.g., specific labs, etc.—at the following link ( https://digitalcommons.wcupa.edu/anthrosoc_facpub/72 ); inquiries or requests for additional information may be sent directly to the first author.

Availability of data and materials

The lab manual can be accessed at the open source link: https://digitalcommons.wcupa.edu/anthrosoc_facpub/72 . Other materials can be obtained from the first author on request.

Abbreviations

West Chester University

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Acknowledgements

The support of the (then) College of Arts and Sciences and its dean, the Provost, and the Office of Sponsored Research and Faculty Development of West Chester University are gratefully acknowledged. In addition, the authors would like to acknowledge the support and counsel of the three external advisors on the project, all biological anthropologists teaching at the three other universities that provided evolution survey comparative data.

This project was supported by an NSF TUES Award (DUE-1245013) and West Chester University.

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Susan L. Johnston, Maureen Knabb, Josh R. Auld & Loretta Rieser-Danner

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SLJ, MK, and JA designed the curriculum. SLJ is the instructor of record for the course and was responsible for obtaining informed consent and for implementing the curriculum. LR-D served as the project evaluator and conducted all analyses. All authors read and approved the final manuscript.

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SLJ is a biological anthropologist and Professor of Anthropology (Department of Anthropology and Sociology); MK is a physiologist and Emeritus Professor of Biology (Department of Biology); JA is an evolutionary biologist and Professor of Biology (Department of Biology); and LR-D is Professor of Psychology (Department of Psychology).

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Supplementary Information

Additional file 1..

Revised version of the evolution survey that includes 25 items; administered at WCU and three other universities from Fall 2014 on.

Additional file 2.

Rubric used to review student laboratory worksheets. Includes 4 measures of scientific thinking (defining the problem, developing a plan to assess the problem, analyzing and presenting information, and interpretating findings and solving the problem), with each assessed on a scale of 4 developmental levels (beginning, developing, appropriately developed, and exemplary).

Additional file 3.

A modified version of the RSQC2 classroom assessment technique (Angelo and Cross, 1993 ), completed by students during and after each laboratory module.

Additional file 4.

A 10-item survey completed by WCU students at both the beginning and the end of each semester asking them to rate their level of confidence in their abilities and/or understanding of several pieces of the scientific process. All items were rated on a 5-point Likert scale: 1 = completely doubtful; 2 = somewhat doubtful; 3 = neutral; 4 = somewhat confident; 5 = strongly confident.

Additional file 5.

Evolution survey, concept scores: descriptive statistics by institution

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Johnston, S.L., Knabb, M., Auld, J.R. et al. Correcting misconceptions about evolution: an innovative, inquiry-based introductory biological anthropology laboratory course improves understanding of evolution compared to instructor-centered courses. Evo Edu Outreach 15 , 6 (2022). https://doi.org/10.1186/s12052-022-00164-4

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Evotourism ®

A Smithsonian magazine special report

AT THE SMITHSONIAN

Seven new things we learned about human evolution in 2021.

Paleoanthropologists Briana Pobiner and Ryan McRae reveal some of the year’s best findings in human origins studies

Briana Pobiner and Ryan McRae

This year—2021—has been a year of progress in overcoming the effects of the Covid-19 pandemic on human evolution research. With some research projects around the world back up and running, we wanted to highlight new and exciting discoveries from 13 different countries on five different continents. Human evolution is the study of what links us all together, and we hope you enjoy these stories we picked to show the geographic and cultural diversity of human evolution research, as well as the different types of evidence for human evolution, including fossils, archaeology, genetics, and even footprints!

New Paranthropus robustus fossils from South Africa show microevolution within a single species.

The human fossil record, like any fossil record, is full of gaps and incomplete specimens that make our understanding of complex evolutionary trends difficult. Identifying species and the process by which new species emerge from fossils falls in the realm of macroevolution , or evolution over broad time scales. These trends and changes tend to be more pronounced and easier to identify in the fossil record; think about how different a Tyrannosaurus rex and a saber-toothed cat are from each other. Human evolution only took place over the course of 5 to 8 million years, a much shorter span compared to the roughly 200 million years since dinosaurs and mammals shared a common ancestor. Because of this, smaller-scale evolutionary changes within a single species or lineage over time, called microevolution , is often difficult to detect.

Fossils of one early human species, Paranthropus robustus , are known from multiple cave sites in South Africa. Like other Paranthropus species, P. robustus is defined by large, broad cheeks, massive molars and premolars, and a skull highly adapted for intense chewing. Fossils of P. robustus from Swartkrans cave, just 20 miles west of Johannesburg, are dated to around 1.8 million years ago and show a distinct sagittal crest, or ridge of bone along the top of the skull, with their jaws indicating a more efficient bite force. Newly discovered fossils of P. robustus from Drimolen cave , about 25 miles north of Johannesburg, described by Jesse Martin from La Trobe University and colleagues in January, are at least 200,000 years older (2.04-1.95 million years old) and have a differently positioned sagittal crest and a less efficient bite force, among other small differences. Despite numerous disparities between fossils at the two sites, they much more closely resemble each other than any other known species of hominin. Because of this, researchers kept them as the same species from two different time points in a single lineage . The differences between fossils at the two sites highlight microevolution within this Paranthropus lineage .

Fossil children from Kenya, France, and South Africa tell us how ancient and modern human burial practices changed over time.

Most of the human fossil record includes the remains of adult individuals; that’s likely because larger and thicker adult bones, and bones of larger individuals, are more likely to survive the burial, fossilization, and discovery processes. The fossil record also gets much richer after the practice of intentional human burial began, starting at least 100,000 years ago .

In November, María Martinón-Torres from CENIEH (National Research Center on Human Evolution) in Spain, Nicole Boivin and Michael Petraglia from the Max Planck Institute for the Science of Human History in Germany, and other colleagues announced the oldest known human burial in Africa —a two-and-a-half to three-year-old child from the site of Panga ya Saidi in Kenya. The child, nicknamed “Mtoto” which means “child" in Kiswahili, was deliberately buried in a tightly flexed position about 78,000 years ago, according to luminescence dating. The way the child’s head was positioned indicates possible burial with a perishable support, like a pillow. In December, a team led by University of Colorado, Denver’s Jaime Hodgkins reported the oldest known burial of a female modern human infant in Europe . She was buried in Arma Veirana Cave in Italy 10,000 years ago with an eagle-owl talon, four shell pendants, and more than 60 shell beads with patterns of wear indicating that adults had clearly worn them for a long time beforehand. This evidence indicates her treatment as a full person by the Mesolithic hunter-gatherer group she belonged to. After extracted DNA determined that she was a girl, the team nicknamed her “Neve” which means “snow” in Italian. Aside from our own species, Neanderthals are also known to sometimes purposefully bury their dead . In December, a team led by Antoine Balzeau from the CNRS (the French National Centre for Scientific Research) and Muséum National d’Histoire Naturelle in France and Asier Gómez-Olivencia from the University of the Basque Country in Spain provided both new and re-studied information on the archaeological context of the La Ferrassie 8 Neanderthal skeleton, a two-year-old buried in France about 41,000 years ago. They conclude that this child, who is one of the most recently directly dated Neanderthals (by Carbon-14) and whose partial skeleton was originally excavated in 1970 and 1973, was purposefully buried . There have also been suggestions that a third species, Homo naledi , known from South Africa between about 335,000 and 236,000 years ago, purposefully buried their dead—though without any ritual context. In November, a team led by University of the Witwatersrand’s Lee Berger published two papers with details of skull and tooth fragments of a four to six-year-old Homo naledi child fossil , nicknamed “Leti” after the Setswana word “letimela” meaning “the lost one.” Given the location of the child’s skull found in a very narrow, remote and inaccessible part of the Rising Star cave system, about a half mile from Swartkrans, this first partial skull of a child of Homo naledi yet recovered might support the idea that this species also deliberately disposed of their dead.

The first Europeans had recent Neanderthal relatives, according to genetic evidence from Czechia and Bulgaria.

Modern humans, Homo sapiens , evolved in Africa and eventually made it to every corner of the world. That is not news. However, we are still understanding how and when the earliest human migrations occurred. We also know that our ancestors interacted with other species of humans at the time, including Neanderthals , based on genetic evidence of Neanderthal DNA in modern humans alive today—an average of 1.9 percent in Europeans.

Remains of some of the earliest humans in Europe were described this year by multiple teams, except they were not fully human. All three of the earliest Homo sapiens in Europe exhibit evidence of Neanderthal interbreeding (admixture) in their recent genealogical past. In April, Kay Prüfer and a team from the Max Planck Institute for the Science of Human History described a human skull from Zlatý kůň, Czechia, dating to around 45,000 years old . This skull contains roughly 3.2 percent Neanderthal DNA in the highly variable regions of the genome, comparable with other humans from around that time. Interestingly, some of these regions indicating Neanderthal admixture were not the same as modern humans, and this individual is not directly ancestral to any population of modern humans, meaning they belonged to a population that has no living descendants. Also in April, Mateja Hajdinjak and a team from the Max Planck Institute for Evolutionary Anthropology described three similar genomes from individuals found in Bacho Kiro Cave, Bulgaria, dating between 46,000 and 42,000 years old . These individuals carry 3.8, 3.4, and 3.0 percent Neanderthal DNA, more than the modern human average. Based on the distribution of these sequences, the team concluded that the three individuals each had a Neanderthal ancestor only six or seven generations back. This is roughly the equivalent length of time from the turn of the twentieth century to today. Interestingly, these three genomes represent two distinct populations of humans that occupied the Bulgarian cave—one of which is directly ancestral to east Asian populations and Indigenous Americans, the other of which is directly ancestral to later western Europeans. These findings suggest that there is continuity of human occupation of Eurasia from the earliest known individuals to present day and that mixing with Neanderthals was likely common, even among different Homo sapiens populations.

A warty pig from Indonesia, a kangaroo from Australia, and a conch shell instrument from France all represent different forms of ancient art.

Currently, the world’s oldest representational or figurative art is a cave painting of a Sulawesi warty pig found in Leang Tedongnge, Indonesia, that was dated to at least 45,500 years ago using Uranium series dating—and reported in January by a team led by Adam Brumm and Maxime Aubert from Griffith University. In February, a team led by Damien Finch from the University of Melbourne in Australia worked with the Balanggarra Aboriginal Corporation, which represents the Traditional Owners of the land in the Kimberly region of Australia, to radiocarbon date mud wasp nests from rock shelters in this area. While there is fossil evidence of modern humans in Australia dating back to at least 50,000 years ago , this team determined that the oldest known Australian Aboriginal figurative rock paintings date back to between around 17,000 and 13,000 years ago . The naturalistic rock paintings mainly depict animals and some plants; the oldest example is of a about 6.5 footlong kangaroo painting on the ceiling of a rock shelter dated to around 17,300 years ago. Right around that time, about 18,000 years ago, an ancient human in France cut off the top of a conch shell and trimmed its jagged outer lip smooth so it could be used as the world’s oldest wind instrument . A team led by Carole Fritz and Gilles Tostello from the Université de Toulouse in France reported in February that they re-examined this shell, discovered in Marsoulas Cave in 1931, using CT scanning. In addition to the modifications described above, they found red fingerprint-sized and shaped dots on the internal surface of the shell, made with ochre pigment also used to create art on the walls of the cave. They also found traces of a wax or resin around the broken opening, which they interpreted as traces of an adhesive used to attach a mouthpiece as found in other conch shell instruments.

Fossil finds from China and Israel complicate the landscape of human diversity in the late Pleistocene.

This year a new species was named from fossil material found in northeast China: Homo longi . A team from Hebei University in China including Qiang Ji, Xijun Ni, Qingfeng Shao and colleagues described this new species dating to at least 146,000 years old. The story behind the discovery of this cranium is fascinating! It was hidden in a well from the Japanese occupying forces in the town of Harbin for 80 years and only recently rediscovered. Due to this history, the dating and provenience of the cranium are difficult to ascertain, but the morphology suggests a mosaic of primitive-like features as seen in Homo heidelbergensis , and other more derived features as seen in Homo sapiens and Neanderthals . Although the cranium closely resembles some other east Asian finds such as the Dali cranium , the team named a new species based on the unique suite of features. This newly named species may represent a distinct new lineage, or may potentially be the first cranial evidence of an enigmatic group of recent human relatives—the Denisovans . Adding to the increasingly complex picture of late Pleistocene Homo are finds from Nesher Ramla in Israel dating to 120,000 to 130,000 years old , described in June by Tel Aviv University’s Israel Hershkovitz and colleagues. Like the Homo longi cranium, the parietal bone, mandible and teeth recovered from Nesher Ramla exhibit a mix of primitive and derived features. The parietal and mandible have stronger affiliations with archaic Homo , such as Homo erectus , while all three parts have features linking them to Neanderthals. Declining to name a new species , the team instead suggests that these finds may represent a link between earlier fossils with “Neanderthal-like features” from Qesem Cave and other sites around 400,000 years ago to later occupation by full Neanderthals closer to 70,000 years ago. Regardless of what these finds may come to represent in the form of new species, they tell us that modern-like traits did not evolve simultaneously, and that the landscape of human interaction in the late Pleistocene was more complex than we realize.

The ghosts of modern humans past were found in DNA in dirt from Denisova Cave in Russia.

Denisova Cave in Russia, which has yielded fossil evidence of Denisovans and Neanderthals (and even remains of a 13-year-old girl who was a hybrid with a Neanderthal mother and Denisovan father), is a paleoanthropological gift that keeps on giving! In June, a team led by Elena Zavala and Matthias Meyer from the Max Planck Institute for Evolutionary Anthropology in Germany and Zenobia Jacobs and Richard Roberts from the University of Wollongong in Australia analyzed DNA from 728 sediment samples from Denisova Cave —the largest analysis ever of sediment DNA from a single excavation site. They found ancient DNA from Denisovans and Neanderthals… and modern humans, whose fossils have not been found there, but who were suspected to have lived there based on Upper Paleolithic jewelry typically made by ancient modern humans found in 45,000-year-old layers there. The study also provided more details about the timing and environmental conditions of occupation of the cave by these three hominin species: first Denisovans were there, between 250,000 and 170,000 years ago; then Neanderthals arrived at the end of this time period (during a colder period) and joined the Denisovans, except between 130,000 and 100,000 years ago (during a warmer period) when only Neanderthal DNA was detected. The Denisovans who came back to the cave after 100,000 years ago have different mitochondrial DNA, suggesting they were from a different population. Finally, modern humans arrived at Denisova Cave by 45,000 years ago. Both fossil and genetic evidence point to a landscape of multiple interacting human species in the late Pleistocene, and it seems like Denisova Cave was the place to be!

Fossilized footprints bring to light new interpretations of behavior and migration in Tanzania, the United States and Spain.

Usually when we think of fossils, we think of the mineralized remnants of bone that represent the skeletons of long since passed organisms. Yet trace fossils, such as fossilized footprints, give us direct evidence of organisms at a specific place in a specific time. The Laetoli footprints , for example, represent the earliest undoubted bipedal hominin, Australopithecus afarensis (Lucy’s species) at 3.6 million years ago. In December, a team led by Ellison McNutt from Ohio University announced that their reanalysis of some of the footprints from Site A at Laetoli were not left by a bear, as had been hypothesized, but by a bipedal hominin. Furthermore, because they are so different from the well-known footprints from Site G, they represent a different bipedal species walking within 1 kilometer (0.6 miles) of each other within the span of a few days! Recently uncovered and dated footprints in White Sands National Park , New Mexico, described in September by a team led by Matthew Bennett of Bournemouth University, place modern humans in the area between 23,000 to 21,000 years ago. Hypotheses as to how Indigenous Americans migrated into North America vary in terms of method (ice-free land corridor versus coastal route) as well as timing. Regardless of the means by which people traveled to North America, migration was highly unlikely, if not impossible, during the last glacial maximum (LGM), roughly 26,000 to 20,000 years ago. These footprints place modern humans south of the ice sheet during this period, meaning that they most likely migrated prior to the LGM . This significantly expands the duration of human occupation past the 13,000 years ago supported by Clovis culture and the roughly 20,000 years ago supported by other evidence. Furthermore, it means that humans and megafauna, like giant ground sloths and wooly mammoths, coexisted for longer than previously thought, potentially lending credit to the theory that their extinction was not caused by humans. Also interesting is that most of these footprints were likely made by children and teenagers, potentially pointing to division of labor within a community. Speaking of footprints left by ancient children, a team led by Eduardo Mayoral from Universidad de Huelva reported 87 Neanderthal footprints from the seaside site of Matalascañas in southwestern Spain in March. Dated at about 106,000 years ago, these are now the oldest Neanderthal footprints in Europe, and possibly in the world. The researchers conclude that of the 36 Neanderthals that left these footprints, 11 were children; the group may have been hunting for birds and small animals, fishing, searching for shellfish… or just frolicking on the seashore. Aw.

A version of this article  was originally published  on the PLOS SciComm blog.

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Briana Pobiner | READ MORE

Briana Pobiner is a paleoanthropologist with the National Museum of Natural History’s Human Origins Program . She lead's the program's education and outreach efforts. 

Ryan McRae | READ MORE

Dr. Ryan McRae is a paleoanthropologist studying the hominin fossil record on a macroscopic scale. He currently works for the National Museum of Natural History’s Human Origins Program as a contractor focusing on research, education, and outreach, and is an adjunct assistant professor of anatomy at the George Washington University School of Medicine and Health Sciences.

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Biology library

Course: biology library   >   unit 25.

• Introduction to evolution and natural selection
• Ape clarification
• Natural selection and the owl butterfly
• Darwin, evolution, & natural selection
• Variation in a species
• Natural selection and Darwin

Evidence for evolution

Key points:.

• Anatomy. Species may share similar physical features because the feature was present in a common ancestor ( homologous structures ).
• Molecular biology. DNA and the genetic code reflect the shared ancestry of life. DNA comparisons can show how related species are.
• Biogeography. The global distribution of organisms and the unique features of island species reflect evolution and geological change.
• Fossils. Fossils document the existence of now-extinct past species that are related to present-day species.
• Direct observation. We can directly observe small-scale evolution in organisms with short lifecycles (e.g., pesticide-resistant insects).

Introduction

Evolution happens on large and small scales.

• Macroevolution , which refers to large-scale changes that occur over extended time periods, such as the formation of new species and groups.
• Microevolution , which refers to small-scale changes that affect just one or a few genes and happen in populations over shorter timescales.

The evidence for evolution

Anatomy and embryology, homologous features, analogous features, determining relationships from similar features, molecular biology.

• The same genetic material (DNA)
• The same, or highly similar, genetic codes
• The same basic process of gene expression (transcription and translation)
• The same molecular building blocks, such as amino acids

Homologous genes

Biogeography, fossil record, direct observation of microevolution.

• Before DDT was applied, a tiny fraction of mosquitos in the population would have had naturally occurring gene versions ( alleles ) that made them resistant to DDT. These versions would have appeared through random mutation , or changes in DNA sequence. Without DDT around, the resistant alleles would not have helped mosquitoes survive or reproduce (and might even have been harmful), so they would have remained rare.
• When DDT spraying began, most of the mosquitos would have been killed by the pesticide. Which mosquitos would have survived? For the most part, only the rare individuals that happened to have DDT resistance alleles (and thus survived being sprayed with DDT). These surviving mosquitoes would have been able to reproduce and leave offspring.
• Over generations, more and more DDT-resistant mosquitoes would have been born into the population. That's because resistant parents would have been consistently more likely to survive and reproduce than non-resistant parents, and would have passed their DDT resistance alleles (and thus, the capacity to survive DDT) on to their offspring. Eventually, the mosquito populations would have bounced back to high numbers, but would have been composed largely of DDT-resistant individuals.
• Homologous structures provide evidence for common ancestry, while analogous structures show that similar selective pressures can produce similar adaptations (beneficial features).
• Similarities and differences among biological molecules (e.g., in the DNA sequence of genes) can be used to determine species' relatedness.
• Biogeographical patterns provide clues about how species are related to each other.
• The fossil record, though incomplete, provides information about what species existed at particular times of Earth’s history.
• Some populations, like those of microbes and some insects, evolve over relatively short time periods and can observed directly.

Attribution:

Works cited:.

• Nothing in biology makes sense except in the light of evolution. (2016, April 6). Retrieved May 15, 2016 from Wikipedia: https://en.wikipedia.org/wiki/Nothing_in_Biology_Makes_Sense_Except_in_the_Light_of_Evolution .
• Wilkin, D. and Akre, B. (2016, March 23). Comparative anatomy and embryology - Advanced. In CK-12 biology advanced concepts . Retrieved from http://www.ck12.org/book/CK-12-Biology-Advanced-Concepts/section/10.22/ .
• Reece, J. B., Urry, L. A., Cain, M. L., Wasserman, S. A., Minorsky, P. V., and Jackson, R. B. (2011). Anatomical and molecular homologies. In Campbell biology (10th ed., p. 474). San Francisco, CA: Pearson.
• Chapman, B. R. and Bolen, E. G. (2015). Convergent evolution [Glossary entry]. In Ecology of North America (2nd ed., p. 311). West Sussex, UK: John Wiley & Sons.
• Insulin. (2014, June 6). In UCSD signaling gateway . Retrieved from http://www.signaling-gateway.org/molecule/query?afcsid=A004315&type=orthologs&adv=latest .
• Wilkin, D. and Akre, B. (2016, March 23). Evolution and the fossil record - Advanced. In CK-12 biology advanced concepts . Retrieved from http://www.ck12.org/book/CK-12-Biology-Advanced-Concepts/section/10.21/ .
• Reece, J. B., Taylor, M. R., Simon, E. J., and Dickey, J. L. (2011). Scientists can observe natural selection in action. In Campbell biology: Concepts & connections (7th ed., p. 259). Boston, MA: Benjamin Cummings.

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• News Releases

Unlocking the secrets of evolution

Norwegian University of Science and Technology

Darwin noted how different finches from the Galapagos Island developed different kinds of beaks, based on the food that they specialized in eating. Later studies showed how rapid fluctuations in seed size over time led to rapid fluctuations in beak size, just as suggested by the new study, published in Science. This illustration is from Darwin, 1845. Journal of researches into the natural history and geology of the countries visited during the voyage of H.M.S. Beagle round the world, under the Command of Capt. Fitz Roy, R.N. 2d edition.

Credit: Illustration: John Gould

Ever since Darwin published his landmark theory of how species evolve, biologists have been fascinated with the intricate mechanisms that make evolution possible.

Can mechanisms responsible for the evolution of a species over a few generations, called microevolution, also explain how species evolve over periods of time extending to thousands or millions of generations, also called macroevolution?

A new paper, just published in Science, shows that the ability of populations to evolve and adapt over a few generations, called evolvability, effectively helps us understand how evolution works on much longer timescales.

By compiling and analysing huge datasets from existing species as well as from fossils, the researchers were able to show that the evolvability responsible for microevolution of many different traits predicts the amount of change observed between populations and species separated by up to one million years.

“Darwin suggested that species gradually evolve, but what we found is that even though populations rapidly evolve over the short term, this (short-term) evolution doesn’t accumulate over time. However, how divergent populations and species are, on average, over long periods of time still depends on their ability to evolve on the short term,” said Christophe Pélabon, a professor at NTNU’s Department of Biology and senior author of the paper.

Big datasets from living creatures and fossils

The ability to respond to selection and to adapt, the evolvability, depends on the amount of heritable (genetic) variation. The researchers conducted their analysis by first compiling a massive dataset with measures of evolvability for living populations and species from publicly available information. They then plotted evolvablity against population and species divergence for different traits such as beak size, number of offspring, flower size and more.

They also examined information from 150 different lineages of fossils, where other researchers had measured differences in morphological traits in the fossils over time periods as short as 10 years and as long as 7.6 million years.

What they saw was that traits with higher evolvability were more divergent among existing populations and species, and that traits with higher evolvability were more likely to be different from each other between two consecutive fossil samples.

Conversely, traits with little evolvability or little variability didn’t change very much between populations or between successive fossil samples

Environmental  fluctuation is the key

Traits with higher evolvability change rapidly because they are able to respond to environmental changes more quickly, Pélabon said.

The environment  – things such as temperature, the type of food available, or any other characteristic important for the survival and the reproduction of the individual – is the driving force of evolutionary changes because populations try to adapt to their own environment.  Typically, environments are changing from year-to-year or decades-to-decades, fluctuating around stable means. This generates fluctuation in the direction of selection.

Highly evolvable traits can rapidly respond to these fluctuations in selection and will fluctuate over time with high amplitude. Traits with little evolvability will also fluctuate but more slowly and thus with lower amplitude.

“Populations, or species, that are geographically distant from each other are exposed to environments whose fluctuations are not synchronized. Consequently, these populations will have different trait values, and the size of this difference will depend on the amplitude of the trait’s fluctuation, and therefore on the evolvability of the trait,” Pélabon said.

Consequences for biodiversity

The researchers’ results suggest that selection and therefore the environment has been relatively stable in the past. With climate change, things are rapidly changing, and mostly in one direction. This may strongly affect patterns of selection and how species can adapt to environments that are still fluctuating but around optima that are no longer stable even over periods of time of a few decades.

“How much species will be able to track these optima and adapt is uncertain, but most likely this will have consequences for biodiversity, even on a short timescale,” he said.

Reference : Agnes Holstad  et al. Evolvability predicts macroevolution under fluctuating selection. Science 384 ,688-693(2024).DOI: 10.1126/science.adi8722

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Evolvability predicts macroevolution under fluctuating selection

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Darwin and His Theory of Evolution

At first glance, Charles Darwin seems an unlikely revolutionary. Growing up a shy and unassuming member of a wealthy British family, he appeared, at least to his father, to be idle and directionless. But even as a child, Darwin expressed an interest in nature. Later, while studying botany at Cambridge University, he was offered a chance to work as an unpaid naturalist on the HMS Beagle , a naval vessel embarking on an exploratory voyage around the world. In the course of nearly five years at sea – during which time the Beagle surveyed the coast of South America and stopped in such places as Australia and, most famously, the Galapagos Islands – Darwin took advantage of countless opportunities to observe plant and animal life and to collect both living and fossilized specimens for later study.

After the Beagle returned to England in October 1836, Darwin began reflecting on his observations and experiences, and over the next two years developed the basic outline of his groundbreaking theory of evolution through natural selection. But beyond sharing his ideas with a close circle of scientist friends, Darwin told no one of his views on the origin and development of life. Indeed, he did not publish his now-famous volume, On the Origin of Species by Means of Natural Selection , until 1859, more than 20 years after he had first formulated his theory.

On the Origin of Species may never have been written, let alone published, if it had not been for Alfred Russel Wallace, another British naturalist who independently proposed a strikingly similar theory in 1858. Wallace’s announcement prompted Darwin to publicly reveal that his own research had led him to the same conclusion decades earlier. This being the age of Victorian gentlemen, it was agreed that the two scientists would jointly publish their writings on the subject. Their work – comprising a collection of Darwin’s earlier notes and an essay by Wallace – was read to the Linnean Society, an association of naturalists, in London on July 1, 1858. The following year, Darwin published On the Origin of Species , a lengthy, fleshed-out treatment of his ideas on evolutionary theory. The book was an immediate bestseller and quickly set off a firestorm of controversy.

Darwin had expected no less – fear of a backlash from Britain’s religious and even scientific establishment had been the primary reason he had delayed publicizing his ideas. Yet the concept of species adaptation was not so radical at the time. Scientists had been debating whether animals evolved decades before Darwin put forth his theory. The idea of “transmutation of species” had been rejected by many prominent naturalists, among them French scientist Georges Cuvier, who believed that species had been created much as they appeared in his day. But transmutation also had early champions, including Darwin’s grandfather, the famed Birmingham physician Erasmus Darwin.

The younger Darwin’s achievement was to offer a plausible and compelling explanation for how species evolve and to use this explanation to trace the history of life’s development. All existing creatures, he argued, descended from a small number of original or progenitor species. Darwin compared the history of life to a great tree, its trunk representing these few common ancestors and an extensive system of branches and twigs symbolizing the great variety of life that has evolved from them.

This evolution, Darwin wrote, is due to two factors. The first factor, Darwin argued, is that each individual animal is marked by subtle differences that distinguish it from its parents. Darwin, who called these differences “variations,” understood their effect but not their cause; the idea of genetic mutation, and indeed the scientific study of genetics, would not arise fully until the early 20th century. The second factor, Darwin argued, is that although variations are random, some of them convey distinct advantages – superior camouflage, a heartier constitution or greater speed, for example – that better equip a creature to survive in its environment. A greater chance of survival allows for more opportunity to breed and pass on advantageous traits to a greater number of offspring. Over time, an advantage spreads throughout a species; in turn, the species is more likely to endure and reproduce. Thus, over the course of many generations, subtle changes occur and accumulate, eventually morphing into bigger changes and, possibly, even a new species.

While Darwin’s ideas initially challenged long-held scientific and religious belief systems, opposition to much of Darwin’s thinking among the scientific communities of the English-speaking world largely collapsed in the decades following the publication of On the Origin of Species . Yet evolution continued to be vigorously rejected by British and American churches because, religious leaders argued, the theory directly contradicted many of the core teachings of the Christian faith.

Darwin’s notion that existing species, including man, had developed over time due to constant and random change seemed to be in clear opposition to the idea that all creatures had been created “according to their kind” by God, as described in the first chapter of the biblical book of Genesis. Before Darwin, the prevailing scientific theory of life’s origins and development had held that species were fixed and that they never changed. This theory, known as “special creationism,” comported well with the biblical account of God creating the fish, fowl and mammals without mention of subsequent alteration.

Darwinian thinking also appeared to contradict the notion, central to Christianity and many other faiths, that man had a special, God-given place in the natural order. Instead, proponents of evolution pointed to signs in human anatomy – remnants of a tailbone, for instance – showing common ancestry with other mammals.

Finally, the idea of a benevolent God who cared for his creation was seemingly challenged by Darwin’s depiction of the natural world as a savage and cruel place – “red in tooth and claw,” as Darwin’s contemporary, Alfred Lord Tennyson, wrote just a few years before On the Origin of Species was published. Darwin’s theory challenged the idea that the natural world existed in benevolent harmony.

Darwin fully understood, and at times agonized over, the threat that his work might pose to traditional religious belief, explaining in an 1860 letter to American botanist Asa Gray that he “had no intention to write atheistically.” But, he went on, “I cannot see as plainly as others do … evidence of design and beneficence on all sides of us. There seems to be too much misery in the world.”

Regardless of his intentions, Darwin’s ideas provoked a harsh and immediate response from religious leaders in Britain. For instance, England’s highest-ranking Catholic official, Henry Cardinal Manning, denounced Darwin’s views as “a brutal philosophy – to wit, there is no God, and the ape is our Adam.” Samuel Wilberforce, the Anglican Archbishop of Oxford and one of the most highly respected religious leaders in 19th-century England, also condemned natural selection in a now-famous speech on what he deemed the theory’s scientific deficiencies at an 1860 meeting of the British Association for the Advancement of Science. At one point during the meeting, Wilberforce reportedly asked biologist Thomas Henry Huxley whether he was related to an ape on his grandmother’s or grandfather’s side. Huxley, whose vigorous defense of evolutionary theory would earn him the nickname “Darwin’s bulldog,” allegedly replied that he would rather be the ancestor of a monkey than an advanced and intelligent human being who employed his “knowledge and eloquence in misrepresenting those who are wearing out their lives in the search for truth.”

Some scholars now contend that Huxley’s rebuke of Wilberforce never occurred. Regardless, it was around this time that the British scientific establishment gained the upper hand in the debate over evolution. And while the public disagreement between ecclesiastical and scientific authorities did not end in the 1860s, religious thinkers became more wary of directly challenging evolution on scientific grounds. In the late 19th and early 20th centuries, churches instead focused much of their energy on resisting the idea that man had evolved from lower animal orders and hence had no special place in creation or, for that matter, a soul. Indeed, while some churches, including the Catholic Church, eventually accepted evolution as a God-directed mechanism of biological development, none questioned the role of God as the sole creator of man.

By the time of his death, in 1882, Darwin was considered the greatest scientist of his age. Moreover, the very church his theory had challenged accorded him a full state funeral and burial in Westminster Abbey, near the grave of Sir Isaac Newton. Darwin’s idea was still provocative, but by the time of his death it had gained general acceptance in Britain, even among many in the Anglican clergy. Indeed, his interment in the abbey was seen by some contemporaries as symbolic of an uneasy truce between science and religion in Britain.

This report was written by David Masci, a senior researcher at the Pew Research Center’s Religion & Public Life Project.

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Do we need a new theory of evolution?

A new wave of scientists argues that mainstream evolutionary theory needs an urgent overhaul. Their opponents have dismissed them as misguided careerists – and the conflict may determine the future of biology

S trange as it sounds, scientists still do not know the answers to some of the most basic questions about how life on Earth evolved. Take eyes, for instance. Where do they come from, exactly? The usual explanation of how we got these stupendously complex organs rests upon the theory of natural selection.

You may recall the gist from school biology lessons. If a creature with poor eyesight happens to produce offspring with slightly better eyesight, thanks to random mutations, then that tiny bit more vision gives them more chance of survival. The longer they survive, the more chance they have to reproduce and pass on the genes that equipped them with slightly better eyesight. Some of their offspring might, in turn, have better eyesight than their parents, making it likelier that they, too, will reproduce. And so on. Generation by generation, over unfathomably long periods of time, tiny advantages add up. Eventually, after a few hundred million years, you have creatures who can see as well as humans, or cats, or owls.

This is the basic story of evolution, as recounted in countless textbooks and pop-science bestsellers. The problem, according to a growing number of scientists, is that it is absurdly crude and misleading.

For one thing, it starts midway through the story, taking for granted the existence of light-sensitive cells, lenses and irises, without explaining where they came from in the first place. Nor does it adequately explain how such delicate and easily disrupted components meshed together to form a single organ. And it isn’t just eyes that the traditional theory struggles with. “The first eye, the first wing, the first placenta. How they emerge. Explaining these is the foundational motivation of evolutionary biology,” says Armin Moczek, a biologist at Indiana University. “And yet, we still do not have a good answer. This classic idea of gradual change, one happy accident at a time, has so far fallen flat.”

There are certain core evolutionary principles that no scientist seriously questions. Everyone agrees that natural selection plays a role, as does mutation and random chance. But how exactly these processes interact – and whether other forces might also be at work – has become the subject of bitter dispute. “If we cannot explain things with the tools we have right now,” the Yale University biologist Günter Wagner told me, “we must find new ways of explaining.”

In 2014, eight scientists took up this challenge, publishing an article in the leading journal Nature that asked “Does evolutionary theory need a rethink?” Their answer was: “Yes, urgently.” Each of the authors came from cutting-edge scientific subfields, from the study of the way organisms alter their environment in order to reduce the normal pressure of natural selection – think of beavers building dams – to new research showing that chemical modifications added to DNA during our lifetimes can be passed on to our offspring. The authors called for a new understanding of evolution that could make room for such discoveries. The name they gave this new framework was rather bland – the Extended Evolutionary Synthesis (EES) – but their proposals were, to many fellow scientists, incendiary.

In 2015, the Royal Society in London agreed to host New Trends in Evolution , a conference at which some of the article’s authors would speak alongside a distinguished lineup of scientists. The aim was to discuss “new interpretations, new questions, a whole new causal structure for biology”, one of the organisers told me. But when the conference was announced, 23 fellows of the Royal Society, Britain’s oldest and most prestigious scientific organisation, wrote a letter of protest to its then president, the Nobel laureate Sir Paul Nurse. “The fact that the society would hold a meeting that gave the public the idea that this stuff is mainstream is disgraceful,” one of the signatories told me. Nurse was surprised by the reaction. “They thought I was giving it too much credibility,” he told me. But, he said: “There’s no harm in discussing things.”

Traditional evolutionary theorists were invited, but few showed up. Nick Barton, recipient of the 2008 Darwin-Wallace medal, evolutionary biology’s highest honour, told me he “decided not to go because it would add more fuel to the strange enterprise”. The influential biologists Brian and Deborah Charlesworth of the University of Edinburgh told me they didn’t attend because they found the premise “irritating”. The evolutionary theorist Jerry Coyne later wrote that the scientists behind the EES were playing “revolutionaries” to advance their own careers. One 2017 paper even suggested some of the theorists behind the EES were part of an “increasing post-truth tendency” within science. The personal attacks and insinuations against the scientists involved were “shocking” and “ugly”, said one scientist, who is nonetheless sceptical of the EES.

What accounts for the ferocity of this backlash? For one thing, this is a battle of ideas over the fate of one of the grand theories that shaped the modern age. But it is also a struggle for professional recognition and status, about who gets to decide what is core and what is peripheral to the discipline. “The issue at stake,” says Arlin Stoltzfus, an evolutionary theorist at the IBBR research institute in Maryland, “is who is going to write the grand narrative of biology.” And underneath all this lurks another, deeper question: whether the idea of a grand story of biology is a fairytale we need to finally give up.

B ehind the current battle over evolution lies a broken dream. In the early 20th century, many biologists longed for a unifying theory that would enable their field to join physics and chemistry in the club of austere, mechanistic sciences that stripped the universe down to a set of elemental rules. Without such a theory, they feared that biology would remain a bundle of fractious sub-fields, from zoology to biochemistry, in which answering any question might require input and argument from scores of warring specialists.

From today’s vantage point, it seems obvious that Darwin’s theory of evolution – a simple, elegant theory that explains how one force, natural selection, came to shape the entire development of life on Earth – would play the role of the great unifier. But at the turn of the 20th century, four decades after the publication of On the Origin of Species and two after his death, Darwin’s ideas were in decline. Scientific collections at the time carried titles such as The Death-bed of Darwinism. Scientists had not lost interest in evolution, but many found Darwin’s account of it unsatisfying. One major problem was that it lacked an explanation of heredity. Darwin had observed that, over time, living things seemed to change to better fit their environment. But he did not understand how these minute changes were passed from one generation to the next.

At the start of the 20th century, the rediscovery of the work of the 19th-century friar and father of genetics, Gregor Mendel, started to provide the answers. Scientists working in the new field of genetics discovered rules that governed the quirks of heredity. But rather than confirm Darwin’s theory, they complicated it. Reproduction appeared to remix genes – the mysterious units that programme the physical traits we end up seeing – in surprising ways. Think of the way a grandfather’s red hair, absent in his son, might reappear in his granddaughter. How was natural selection meant to function when its tiny variations might not even reliably pass from parent to offspring every time?

Even more ominous for Darwinists was the emergence of the “mutationists” in the 1910s, a school of geneticists whose star exponent, Thomas Hunt Morgan, showed that by breeding millions of fruit flies – and sometimes spiking their food with the radioactive element radium – he could produce mutated traits, such as new eye colours or additional limbs. These were not the tiny random variations on which Darwin’s theory was built, but sudden, dramatic changes. And these mutations, it turned out, were heritable. The mutationists believed that they had identified life’s true creative force. Sure, natural selection helped to remove unsuitable changes, but it was simply a humdrum editor for the flamboyant poetry of mutation. “ Natura non facit saltum ,” Darwin had once written: “Nature does not make jumps.” The mutationists begged to differ.

These disputes over evolution had the weight of a theological schism. At stake were the forces governing all creation. For Darwinists especially, their theory was all-or-nothing. If another force, apart from natural selection, could also explain the differences we see between living things, Darwin wrote in On the Origin of Species, his whole theory of life would “utterly break down”. If the mutationists were right, instead of a single force governing all biological change, scientists would have to dig deep into the logic of mutation. Did it work differently on legs and lungs? Did mutations in frogs work differently to mutations in owls or elephants?

In 1920, the philosopher Joseph Henry Woodger wrote that biology suffered from “fragmentation” and “cleavages” that would be “unknown in such a well-unified science as, for example, chemistry”. The divergent groups often feuded, he noted, and it seemed to be getting worse. It began to seem inevitable that the life sciences would grow more and more fractured, and the possibility of a common language would slip away.

J ust as it seemed that Darwinism might be buried, a curious collection of statisticians and animal breeders came along to revitalise it. In the 1920s and 30s, working separately but in loose correspondence, thinkers such as the British father of scientific statistics, Ronald Fisher, and the American geneticist Sewall Wright, proposed a revised theory of evolution that accounted for scientific advances since Darwin’s death but still promised to explain all of life’s mysteries with a few simple rules. In 1942, the English biologist Julian Huxley coined the name for this theory: the modern synthesis. Eighty years on, it still provides the basic framework for evolutionary biology as it is taught to millions of schoolchildren and undergraduates every year. Insofar as a biologist works in the tradition of the modern synthesis, they are considered “mainstream”; insofar as they reject it, they are considered marginal.

Despite the name, it was not actually a synthesis of two fields, but a vindication of one in light of the other. By building statistical models of animal populations that accounted for the laws of genetics and mutation, the modern synthesists showed that, over long periods of time, natural selection still functioned much as Darwin had predicted. It was still the boss. In the fullness of time, mutations were too rare to matter, and the rules of heredity didn’t affect the overall power of natural selection. Through a gradual process, genes with advantages were preserved over time, while others that didn’t confer advantages disappeared.

Rather than getting stuck into the messy world of individual organisms and their specific environments, proponents of the modern synthesis observed from the lofty perspective of population genetics. To them, the story of life was ultimately just the story of clusters of genes surviving or dying out over the grand sweep of evolutionary time.

The modern synthesis arrived at just the right time. Beyond its explanatory power, there were two further reasons – more historical, or even sociological, than scientific – why it took off. First, the mathematical rigour of the synthesis was impressive, and not seen before in biology. As the historian Betty Smocovitis points out, it brought the field closer to “examplar sciences” such as physics. At the same time, writes Smocovitis, it promised to unify the life sciences at a moment when the “enlightenment project” of scientific unification was all the rage. In 1946, the biologists Ernst Mayr and George Gaylord Simpson started the Society for the Study of Evolution , a professional organisation with its own journal, which Simpson said would bring together the sub-fields of biology on “the common ground of evolutionary studies”. This was all possible, he later reflected , because “we seem at last to have a unified theory […] capable of facing all the classic problems of the history of life and of providing a causalistic solution of each.”

This was a time when biology was ascending to its status as a major science. University departments were forming, funding was flowing in, and thousands of newly accredited scientists were making thrilling discoveries. In 1944, the Canadian-American biologist Oswald Avery and his colleagues had proved that DNA was the physical substance of genes and heredity, and in 1953 James Watson and Francis Crick – leaning heavily on work from Rosalind Franklin and the American chemist Linus Pauling – mapped its double-helical structure.

While information piled up at a rate that no scientist could fully digest, the steady thrum of the modern synthesis ran through it all. The theory dictated that, ultimately, genes built everything, and natural selection scrutinised every bit of life for advantage. Whether you were looking at algae blooming in a pond or peacock mating rituals, it could all be understood as natural selection doing its work on genes. The world of life could seem suddenly simple again.

By 1959, when the University of Chicago held a conference celebrating the centennial of the publication of On the Origin of Species, the modern synthesists were triumphant. The venues were packed and national newspaper reporters followed the proceedings. (Queen Elizabeth was invited, but sent her apologies.) Huxley crowed that “this is one of the first public occasions on which it has been frankly faced that all aspects of reality are subject to evolution”.

Yet soon enough, the modern synthesis would come under assault from scientists within the very departments that the theory had helped build.

F rom the start, there had always been dissenters. In 1959, the developmental biologist CH Waddington lamented that the modern synthesis had sidelined valuable theories in favour of “drastic simplifications which are liable to lead us to a false picture of how the evolutionary process works”. Privately, he complained that anyone working outside the new evolutionary “party line” – that is, anyone who didn’t embrace the modern synthesis – was ostracised.

Then came a devastating series of new findings that called into question the theory’s foundations. These discoveries, which began in the late 60s, came from molecular biologists. While the modern synthesists looked at life as if through a telescope, studying the development of huge populations over immense chunks of time, the molecular biologists looked through a microscope, focusing on individual molecules. And when they looked, they found that natural selection was not the all-powerful force that many had assumed it to be.

They found that the molecules in our cells – and thus the sequences of the genes behind them – were mutating at a very high rate. This was unexpected, but not necessarily a threat to mainstream evolutionary theory. According to the modern synthesis, even if mutations turned out to be common, natural selection would, over time, still be the primary cause of change, preserving the useful mutations and junking the useless ones. But that isn’t what was happening. The genes were changing – that is, evolving – but natural selection wasn’t playing a part. Some genetic changes were being preserved for no reason apart from pure chance. Natural selection seemed to be asleep at the wheel.

Evolutionary biologists were stunned. In 1973, David Attenborough presented a BBC documentary that included an interview with one of the leading modern synthesists, Theodosius Dobzhansky. He was visibly distraught at the “non-Darwinian evolution” that some scientists were now proposing. “If this were so, evolution would have hardly any meaning, and would not be going anywhere in particular,” he said. “This is not simply a quibble among specialists. To a man looking for the meaning of his existence, evolution by natural selection makes sense.” Where once Christians had complained that Darwin’s theory made life meaningless, now Darwinists levelled the same complaint at scientists who contradicted Darwin.

Other assaults on evolutionary orthodoxy followed. The influential palaeontologists Stephen Jay Gould and Niles Eldredge argued that the fossil record showed evolution often happened in short, concentrated bursts; it didn’t have to be slow and gradual. Other biologists simply found that the modern synthesis had little relevance to their work. As the study of life increased in complexity, a theory based on which genes were selected in various environments started to seem beside the point. It didn’t help answer questions such as how life emerged from the seas, or how complex organs, such as the placenta, developed. Using the lens of the modern synthesis to explain the latter, says the Yale developmental biologist Günter Wagner, would be “like using thermodynamics to explain how the brain works”. (The laws of thermodynamics, which explain how energy is transferred, do apply to the brain, but they aren’t much help if you want to know how memories are formed or why we experience emotion.)

Just as feared, the field split. In the 70s, molecular biologists in many universities peeled off from biology departments to form their own separate departments and journals. Some in other sub-fields, such as palaeontology and developmental biology, drifted away as well. Yet the biggest field of all, mainstream evolutionary biology, continued much as before. The way the champions of the modern synthesis – who by this point dominated university biology departments – dealt with potentially destabilising new findings was by acknowledging that such processes happen sometimes (subtext: rarely), are useful to some specialists (subtext: obscure ones), but do not fundamentally alter the basic understanding of biology that descends from the modern synthesis (subtext: don’t worry about it, we can continue as before). In short, new discoveries were often dismissed as little more than mildly diverting curiosities.

Today, the modern synthesis “remains, mutatis mutandis , the core of modern evolutionary biology” wrote the evolutionary theorist Douglas Futuyma in a 2017 paper defending the mainstream view. The current version of the theory allows some room for mutation and random chance, but still views evolution as the story of genes surviving in vast populations. Perhaps the biggest change from the theory’s mid-century glory days is that its most ambitious claims – that simply by understanding genes and natural selection, we can understand all life on earth – have been dropped, or now come weighted with caveats and exceptions. This shift has occurred with little fanfare. The theory’s ideas are still deeply embedded in the field, yet no formal reckoning with its failures or schisms has occurred. To its critics, the modern synthesis occupies a position akin to a president reneging on a campaign promise – it failed to satisfy its entire coalition, but remains in office, hands on the levers of power, despite its diminished offer.

Brian and Deborah Charlesworth are considered by many to be high priests of the tradition that descends from the modern synthesis. They are eminent thinkers, who have written extensively on the place of new theories in evolutionary biology, and they don’t believe any radical revision is needed. Some argue that they are too conservative, but they insist they are simply careful – cautious about dismantling a tried-and-tested framework in favour of theories that lack evidence. They are interested in fundamental truths about evolution, not explaining every diverse result of the process.

“We’re not here to explain the elephant’s trunk, or the camel’s hump. If such explanations could even be possible,” Brian Charlesworth told me. Instead, he said, evolutionary theory should be universal, focusing on the small number of factors that apply to how every living thing develops. “It’s easy to get hung up on ‘you haven’t explained why a particular system works the way it does’. But we don’t need to know,” Deborah told me. It’s not that the exceptions are uninteresting; it’s just that they aren’t all that important.

K evin Laland, the scientist who organised the contentious Royal Society conference, believes it is time for proponents of neglected evolutionary sub-fields to band together. Laland and his fellow proponents of the Extended Evolutionary Synthesis, the EES, call for a new way of thinking about evolution – one that starts not by seeking the simplest explanation, or the universal one, but what combination of approaches offers the best explanation to biology’s major questions. Ultimately, they want their sub-fields – plasticity, evolutionary development, epigenetics, cultural evolution – not just recognised, but formalised in the canon of biology.

There are some firebrands among this group. The geneticist Eva Jablonka has proclaimed herself a neo-Lamarckist, after Jean-Baptiste Lamarck, the 19th-century populariser of pre-Darwinian ideas of inheritance, who has often been seen as a punchline in the history of science. Meanwhile, the physiologist Denis Noble has called for a “revolution” against traditional evolutionary theory. But Laland, a lead author on many of the movement’s papers, insists that they simply want to expand the current definition of evolution. They are reformers, not revolutionaries.

The case for EES rests on a simple claim: in the past few decades, we have learned many remarkable things about the natural world – and these things should be given space in biology’s core theory. One of the most fascinating recent areas of research is known as plasticity, which has shown that some organisms have the potential to adapt more rapidly and more radically than was once thought. Descriptions of plasticity are startling, bringing to mind the kinds of wild transformations you might expect to find in comic books and science fiction movies.

Emily Standen is a scientist at the University of Ottawa, who studies Polypterus senegalus , AKA the Senegal bichir, a fish that not only has gills but also primitive lungs. Regular polypterus can breathe air at the surface, but they are “much more content” living underwater, she says. But when Standen took Polypterus that had spent their first few weeks of life in water, and subsequently raised them on land, their bodies began to change immediately. The bones in their fins elongated and became sharper, able to pull them along dry land with the help of wider joint sockets and larger muscles. Their necks softened. Their primordial lungs expanded and their other organs shifted to accommodate them. Their entire appearance transformed. “They resembled the transition species you see in the fossil record, partway between sea and land,” Standen told me. According to the traditional theory of evolution, this kind of change takes millions of years. But, says Armin Moczek, an extended synthesis proponent, the Senegal bichir “is adapting to land in a single generation”. He sounded almost proud of the fish.

Moczek’s own area of expertise is dung beetles, another remarkably plastic species. With future climate change in mind, he and his colleagues tested the beetles’ response to different temperatures. Colder weather makes it harder for the beetles to take off. But the researchers found that they responded to these conditions by growing larger wings. The crucial thing about such observations, which challenge the traditional understanding of evolution, is that these sudden developments all come from the same underlying genes. The species’s genes aren’t being slowly honed, generation by generation. Rather, during its early development it has the potential to grow in a variety of ways, allowing it to survive in different situations.

“We believe this is ubiquitous across species,” says David Pfennig of the University of North Carolina at Chapel Hill. He works on spadefoot toads, amphibians the size of a Matchbox car. Spadefoots are normally omnivorous, but spadefoot tadpoles raised solely on meat grow larger teeth, more powerful jaws, and a hardy, more complex gut. Suddenly, they resemble a powerful carnivore, feeding on hardy crustaceans, and even other tadpoles.

Plasticity doesn’t invalidate the idea of gradual change through selection of small changes, but it offers another evolutionary system with its own logic working in concert. To some researchers, it may even hold the answers to the vexed question of biological novelties: the first eye, the first wing. “Plasticity is perhaps what sparks the rudimentary form of a novel trait,” says Pfennig.

Plasticity is well accepted in developmental biology, and the pioneering theorist Mary Jane West-Eberhard began making the case that it was a core evolutionary force in the early 00s. And yet, to biologists in many other fields, it is virtually unknown. Undergraduates beginning their education are unlikely to hear anything about it, and it has still to make much mark in popular science writing.

Biology is full of theories like this. Other interests of the EES include extra-genetic inheritance, known as epigenetics. This is the idea that something – say a psychological injury, or a disease – experienced by a parent attaches small chemical molecules to their DNA that are repeated in their children. This has been shown to happen in some animals across multiple generations, and caused controversy when it was suggested as an explanation for intergenerational trauma in humans. Other EES proponents track the inheritance of things like culture – as when groups of dolphins develop and then teach each other new hunting techniques – or the communities of helpful microbes in animal guts or plant roots, which are tended to and passed on through generations like a tool. In both cases, researchers contend that these factors might impact evolution enough to warrant a more central role. Some of these ideas have become briefly fashionable, but remain disputed. Others have sat around for decades, offering their insights to a small audience of specialists and no one else. Just like at the turn of the 20th century, the field is split into hundreds of sub-fields, each barely aware of the rest.

To the EES group, this is a problem that urgently needs to be solved – and the only solution is a more capacious unifying theory. These scientists are keen to expand their research and gather the data to disprove their doubters. But they are also aware that logging results in the literature may not be enough. “Parts of the modern synthesis are deeply ingrained in the whole scientific community, in funding networks, positions, professorships,” says Gerd B Müller, head of the Department of Theoretical Biology at the university of Vienna and a major backer of the EES. “It’s a whole industry.”

The modern synthesis was such a seismic event that even its flatly wrong ideas took up to half a century to correct. The mutationists were so thoroughly buried that even after decades of proof that mutation was, in fact, a key part of evolution, their ideas were still regarded with suspicion. As recently as 1990, one of the most influential university evolution textbooks could claim that “the role of new mutations is not of immediate significance” – something that very few scientists then, or now, actually believe. Wars of ideas are not won with ideas alone.

To release biology from the legacy of the modern synthesis, explains Massimo Pigliucci, a former professor of evolution at Stony Brook University in New York, you need a range of tactics to spark a reckoning: “Persuasion, students taking up these ideas, funding, professorial positions.” You need hearts as well as minds. During a Q&A with Pigliucci at a conference in 2017, one audience member commented that the disagreement between EES proponents and more conservative biologists sometimes looked more like a culture war than a scientific disagreement. According to one attender, “Pigliucci basically said: ‘Sure, it’s a culture war, and we’re going to win it,’ and half the room burst out cheering.”

T o some scientists, though, the battle between traditionalists and extended synthesists is futile. Not only is it impossible to make sense of modern biology, they say, it is unnecessary. Over the past decade the influential biochemist Ford Doolittle has published essays rubbishing the idea that the life sciences need codification. “We don’t need no friggin’ new synthesis. We didn’t even really need the old synthesis,” he told me.

What Doolittle and like-minded scientists want is more radical: the death of grand theories entirely. They see such unifying projects as a mid-century – even modernist – conceit, that have no place in the postmodern era of science. The idea that there could be a coherent theory of evolution is “an artefact of how biology developed in the 20th century, probably useful at the time,” says Doolittle. “But not now.” Doing right by Darwin isn’t about venerating all his ideas, he says, but building on his insight that we can explain how present life forms came from past ones in radical new ways.

Doolittle and his allies, such as the computational biologist Arlin Stoltzfus, are descendants of the scientists who challenged the modern synthesis from the late 60s onwards by emphasising the importance of randomness and mutation . The current superstar of this view, known as neutral evolution, is Michael Lynch, a geneticist at the University of Arizona. Lynch is soft-spoken in conversation, but unusually pugnacious in what scientists call “the literature”. His books rail against scientists who accept the status quo and fail to appreciate the rigorous mathematics that undergirds his work. “For the vast majority of biologists, evolution is nothing more than natural selection,” he wrote in 2007. “This blind acceptance […] has led to a lot of sloppy thinking, and is probably the primary reason why evolution is viewed as a soft science by much of society.” (Lynch is also not a fan of the EES. If it were up to him, biology would be even more reductive than the modern synthesists imagined.)

What Lynch has shown, over the past two decades, is that many of the complex ways DNA is organised in our cells probably happened at random. Natural selection has shaped the living world, he argues, but so too has a sort of formless cosmic drifting that can, from time to time, assemble order from chaos. When I spoke to Lynch, he said he would continue to extend his work to as many fields of biology as possible – looking at cells, organs, even whole organisms – to prove that these random processes were universal.

As with so many of the arguments that divide evolutionary biologists today, this comes down to a matter of emphasis. More conservative biologists do not deny that random processes occur, but believe they’re much less important than Doolittle or Lynch think.

The computational biologist Eugene Koonin thinks people should get used to theories not fitting together. Unification is a mirage. “In my view there is no – can be no – single theory of evolution,” he told me. “There cannot be a single theory of everything. Even physicists do not have a theory of everything.”

This is true. Physicists agree that the theory of quantum mechanics applies to very tiny particles, and Einstein’s theory of general relativity applies to larger ones. Yet the two theories appear incompatible. Late in life, Einstein hoped to find a way to unify them. He died unsuccessful. In the next few decades, other physicists took up the same task, but progress stalled, and many came to believe it might be impossible. If you ask a physicist today about whether we need a unifying theory, they would probably look at you with puzzlement. What’s the point, they might ask. The field works, the work continues.

This article was amended on 4 July 2022. An earlier version described Sewall Wright as a livestock breeder. To clarify, Wright spent a decade as a senior animal husbandman for the US Department of Agriculture before becoming a professor at the University of Chicago.

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New research shows microevolution can be used to predict how evolution works on much longer timescales

by Nancy Bazilchuk, Norwegian University of Science and Technology

Ever since Charles Darwin published his landmark theory of how species evolve, biologists have been fascinated with the intricate mechanisms that make evolution possible.

Can mechanisms responsible for the evolution of a species over a few generations, called microevolution, also explain how species evolve over periods of time extending to thousands or millions of generations, also called macroevolution?

A new paper, just published in Science , shows that the ability of populations to evolve and adapt over a few generations, called evolvability, effectively helps us understand how evolution works on much longer timescales.

By compiling and analyzing huge datasets from existing species as well as from fossils, the researchers were able to show that the evolvability responsible for microevolution of many different traits predicts the amount of change observed between populations and species separated by up to one million years.

"Darwin suggested that species gradually evolve, but what we found is that even though populations rapidly evolve over the short term, this (short-term) evolution doesn't accumulate over time. However, how divergent populations and species are, on average, over long periods of time still depends on their ability to evolve on the short term," said Christophe Pélabon, a professor at NTNU's Department of Biology and senior author of the paper.

Big datasets from living creatures and fossils

The ability to respond to selection and to adapt, the evolvability, depends on the amount of heritable (genetic) variation. The researchers conducted their analysis by first compiling a massive dataset with measures of evolvability for living populations and species from publicly available information. They then plotted evolvablity against population and species divergence for different traits such as [bird] beak size, number of offspring, [plant] flower size and more.

They also examined information from 150 different lineages of fossils, where other researchers had measured differences in morphological traits in the fossils over time periods as short as 10 years and as long as 7.6 million years.

What they saw was that traits with higher evolvability were more divergent among existing populations and species, and that traits with higher evolvability were more likely to be different from each other between two consecutive fossil samples.

Conversely, traits with little evolvability or little variability didn't change very much between populations or between successive fossil samples

Environmental fluctuation is the key

Traits with higher evolvability change rapidly because they are able to respond to environmental changes more quickly, Pélabon said.

The environment—things such as temperature, the type of food available, or any other characteristic important for the survival and the reproduction of the individual—is the driving force of evolutionary changes because populations try to adapt to their own environment. Typically, environments are changing from year to year or decade to decade, fluctuating around stable means. This generates fluctuation in the direction of selection.

Highly evolvable traits can rapidly respond to these fluctuations in selection and will fluctuate over time with high amplitude. Traits with little evolvability will also fluctuate but more slowly and thus with lower amplitude.

"Populations or species that are geographically distant from each other are exposed to environments whose fluctuations are not synchronized. Consequently, these populations will have different trait values, and the size of this difference will depend on the amplitude of the trait's fluctuation, and therefore on the evolvability of the trait," Pélabon said.

Consequences for biodiversity

The researchers' results suggest that selection and therefore the environment has been relatively stable in the past. With climate change , things are rapidly changing, and mostly in one direction. This may strongly affect patterns of selection and how species can adapt to environments that are still fluctuating but around optima that are no longer stable even over periods of time of a few decades.

"How much species will be able to track these optima and adapt is uncertain, but most likely this will have consequences for biodiversity, even on a short timescale," he said.

Journal information: Science

Provided by Norwegian University of Science and Technology

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