hypothesis for natural selection lab

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Natural Selection Lab

Natural selection lab ideas.

Natural selection is a fundamental concept in biology, but it can be challenging for students who struggle to wrap their heads around the enormous time scale that we often use. I want to make things easy, efficient and engaging. Using hands-on activities can encourage even the most reluctant student interested. Here are a few ways to make your next natural selection lab more fun!

5 ways to make your natural selection lab more fun:

Play “survival of the fittest” games.

Create games that simulate the concept of survival of the fittest. For example, you can have students pick beads or balls out of jar in teams and those who finish first get a prize (in terms of biology this means they would pass on their genes). Each team could be given a different object to collect the beads with and they will quickly be able to see that not all objects are equally fit for the job. Explain how this game represents how organisms that are better adapted to their environment have a better chance of surviving and reproducing.

Use examples from pop culture

Use what they know. Great examples of mutations and adaptations include traditional superhero stories. For example, you can discuss how the X-Men’s mutant powers increase their fitness and give them an advantage in terms of natural selection. This makes the topic more relatable and engaging for students.

Other connections:

• Wonder Woman

Conduct experiments

Experiments are an excellent way to make lessons on natural selection fun and interactive. You can have students conduct an experiment where they simulate natural selection by selecting beans of different colors from a container. The beans represent a population of organisms, and the different colors represent variations in traits. Students can see how the population changes over time based on their selections.

Use Technology

Using technology can make lessons on natural selection more interactive and engaging. Google free natural selection simulations for the most current options. I found one with a great video covering terms at Generation Genius. For example, you can use online simulations that allow students to see how different factors, such as predation or resource availability, affect the survival and reproduction of organisms. These simulations can help students visualize the concept of natural selection in action.

Don’t forget that kids need a chance to gain vocabulary, practice applying, and recalling their knowledge to prepare for end of year testing and college admissions.

Role-Playing Activities for your Natural Selection Lab Time

Role-playing activities can make lessons on natural selection more fun and memorable. For example, you can assign students different roles, such as predator or prey, and have them act out scenarios that illustrate natural selection.

I love using the Oh Deer game f or this. If you don’t have a large space to play this, you can give the kids resource cards (I usually have just tear up different colored papers to represent the different resources). At each round, I ask them to hold up a card and look around. Then I hold up a card. If their card matches, they get to keep it. If their card doesn’t, then they forfeit that card (either to another play or me). I have a follow up resource so students can see these types of changes in action and apply it to tables, graphs, charts, and carrying capacity. This makes the topic more interactive and engaging for students.

More Ideas for your Natural Selection Lab

Teaching natural selection can be challenging, but there are many fun and engaging ways to make it more interesting for your students. Here are some ideas:

• Peppered moth simulation: One classic example of natural selection is the story of the peppered moth, which changed color from light to dark during the Industrial Revolution in England. You can simulate this process by placing light and dark-colored paper moths on a tree trunk, and then letting students “predator” students remove the easier-to-spot moths. I also find this works very well using white and brown rice in a white container or white paper towel and tweezers or clothespins. After several rounds, the ratio of light to dark moths should reflect the selective pressure.
• Bird beak adaptation: Another classic example of natural selection is the different beak shapes of finches in the Galapagos Islands. You can demonstrate this by having students use different tools (tweezers, pliers, chopsticks, etc.) to try to pick up different types of food (beans, rice, seeds, etc.). The tool that works best for each food item represents the beak adaptation of a particular bird species. I do this with whatever I have hanging around. I gave you more details in a Reel on IG.

View this post on Instagram A post shared by Kim | The Learning Hypothesis (@learninghypothesis)

• Case studies: You can have students read and analyze case studies of natural selection in action, such as the evolution of antibiotic resistance in bacteria or the evolution of pesticide resistance in insects. This can help them understand how natural selection operates in real-world scenarios.

By using these and other fun and engaging teaching methods, you can help your students better understand and appreciate the concept of natural selection and biology as a whole.

Looking for other ideas ?

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Volume 2 Supplement 2

Special Issue: Transitional Fossils

• Evolutionary Concepts
• Open access
• Published: 09 April 2009

Understanding Natural Selection: Essential Concepts and Common Misconceptions

• T. Ryan Gregory 1  

Evolution: Education and Outreach volume  2 ,  pages 156–175 ( 2009 ) Cite this article

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Natural selection is one of the central mechanisms of evolutionary change and is the process responsible for the evolution of adaptive features. Without a working knowledge of natural selection, it is impossible to understand how or why living things have come to exhibit their diversity and complexity. An understanding of natural selection also is becoming increasingly relevant in practical contexts, including medicine, agriculture, and resource management. Unfortunately, studies indicate that natural selection is generally very poorly understood, even among many individuals with postsecondary biological education. This paper provides an overview of the basic process of natural selection, discusses the extent and possible causes of misunderstandings of the process, and presents a review of the most common misconceptions that must be corrected before a functional understanding of natural selection and adaptive evolution can be achieved.

“There is probably no more original, more complex, and bolder concept in the history of ideas than Darwin's mechanistic explanation of adaptation.” Ernst Mayr ( 1982 , p.481)

Introduction

Natural selection is a non-random difference in reproductive output among replicating entities, often due indirectly to differences in survival in a particular environment, leading to an increase in the proportion of beneficial, heritable characteristics within a population from one generation to the next. That this process can be encapsulated within a single (admittedly lengthy) sentence should not diminish the appreciation of its profundity and power. It is one of the core mechanisms of evolutionary change and is the main process responsible for the complexity and adaptive intricacy of the living world. According to philosopher Daniel Dennett ( 1995 ), this qualifies evolution by natural selection as “the single best idea anyone has ever had.”

Natural selection results from the confluence of a small number of basic conditions of ecology and heredity. Often, the circumstances in which those conditions apply are of direct significance to human health and well-being, as in the evolution of antibiotic and pesticide resistance or in the impacts of intense predation by humans (e.g., Palumbi 2001 ; Jørgensen et al. 2007 ; Darimont et al. 2009 ). Understanding this process is therefore of considerable importance in both academic and pragmatic terms. Unfortunately, a growing list of studies indicates that natural selection is, in general, very poorly understood—not only by young students and members of the public but even among those who have had postsecondary instruction in biology.

As is true with many other issues, a lack of understanding of natural selection does not necessarily correlate with a lack of confidence about one's level of comprehension. This could be due in part to the perception, unfortunately reinforced by many biologists, that natural selection is so logically compelling that its implications become self-evident once the basic principles have been conveyed. Thus, many professional biologists may agree that “[evolution] shows how everything from frogs to fleas got here via a few easily grasped biological processes ” (Coyne 2006 ; emphasis added). The unfortunate reality, as noted nearly 20 years ago by Bishop and Anderson ( 1990 ), is that “the concepts of evolution by natural selection are far more difficult for students to grasp than most biologists imagine.” Despite common assumptions to the contrary by both students and instructors, it is evident that misconceptions about natural selection are the rule, whereas a working understanding is the rare exception.

The goal of this paper is to enhance (or, as the case may be, confirm) readers' basic understanding of natural selection. This first involves providing an overview of the basis and (one of the) general outcomes of natural selection as they are understood by evolutionary biologists Footnote 1 . This is followed by a brief discussion of the extent and possible causes of difficulties in fully grasping the concept and consequences of natural selection. Finally, a review of the most widespread misconceptions about natural selection is provided. It must be noted that specific instructional tools capable of creating deeper understanding among students generally have remained elusive, and no new suggestions along these lines are presented here. Rather, this article is aimed at readers who wish to confront and correct any misconceptions that they may harbor and/or to better recognize those held by most students and other non-specialists.

The Basis and Basics of Natural Selection

Though rudimentary forms of the idea had been presented earlier (e.g., Darwin and Wallace 1858 and several others before them), it was in On the Origin of Species by Means of Natural Selection that Darwin ( 1859 ) provided the first detailed exposition of the process and implications of natural selection Footnote 2 . According to Mayr ( 1982 , 2001 ), Darwin's extensive discussion of natural selection can be distilled to five “facts” (i.e., direct observations) and three associated inferences. These are depicted in Fig.  1 .

The basis of natural selection as presented by Darwin ( 1859 ), based on the summary by Mayr ( 1982 )

Some components of the process, most notably the sources of variation and the mechanisms of inheritance, were, due to the limited available information in Darwin's time, either vague or incorrect in his original formulation. Since then, each of the core aspects of the mechanism has been elucidated and well documented, making the modern theory Footnote 3 of natural selection far more detailed and vigorously supported than when first proposed 150 years ago. This updated understanding of natural selection consists of the elements outlined in the following sections.

Overproduction, Limited Population Growth, and the “Struggle for Existence”

A key observation underlying natural selection is that, in principle, populations have the capacity to increase in numbers exponentially (or “geometrically”). This is a simple function of mathematics: If one organism produces two offspring, and each of them produces two offspring, and so on, then the total number grows at an increasingly rapid rate (1 → 2 → 4 → 8 → 16 → 32 → 64... to 2 n after n rounds of reproduction).

The enormity of this potential for exponential growth is difficult to fathom. For example, consider that beginning with a single Escherichia coli bacterium, and assuming that cell division occurs every 30 minutes, it would take less than a week for the descendants of this one cell to exceed the mass of the Earth. Of course, exponential population expansion is not limited to bacteria. As Nobel laureate Jacques Monod once quipped, “What is true for E. coli is also true for the elephant,” and indeed, Darwin ( 1859 ) himself used elephants as an illustration of the principle of rapid population growth, calculating that the number of descendants of a single pair would swell to more than 19,000,000 in only 750 years Footnote 4 . Keown ( 1988 ) cites the example of oysters, which may produce as many as 114,000,000 eggs in a single spawn. If all these eggs grew into oysters and produced this many eggs of their own that, in turn, survived to reproduce, then within five generations there would be more oysters than the number of electrons in the known universe.

Clearly, the world is not overrun with bacteria, elephants, or oysters. Though these and all other species engage in massive overproduction (or “superfecundity”) and therefore could in principle expand exponentially, in practice they do not Footnote 5 . The reason is simple: Most offspring that are produced do not survive to produce offspring of their own. In fact, most population sizes tend to remain relatively stable over the long term. This necessarily means that, on average, each pair of oysters produces only two offspring that go on to reproduce successfully—and that 113,999,998 eggs per female per spawn do not survive (see also Ridley 2004 ). Many young oysters will be eaten by predators, others will starve, and still others will succumb to infection. As Darwin ( 1859 ) realized, this massive discrepancy between the number of offspring produced and the number that can be sustained by available resources creates a “struggle for existence” in which often only a tiny fraction of individuals will succeed. As he noted, this can be conceived as a struggle not only against other organisms (especially members of the same species, whose ecological requirements are very similar) but also in a more abstract sense between organisms and their physical environments.

Variation and Inheritance

Variation among individuals is a fundamental requirement for evolutionary change. Given that it was both critical to his theory of natural selection and directly counter to much contemporary thinking, it should not be surprising that Darwin ( 1859 ) expended considerable effort in attempting to establish that variation is, in fact, ubiquitous. He also emphasized the fact that some organisms—namely relatives, especially parents and their offspring—are more similar to each other than to unrelated members of the population. This, too, he realized is critical for natural selection to operate. As Darwin ( 1859 ) put it, “Any variation which is not inherited is unimportant for us.” However, he could not explain either why variation existed or how specific characteristics were passed from parent to offspring, and therefore was forced to treat both the source of variation and the mechanism of inheritance as a “black box.”

The workings of genetics are no longer opaque. Today, it is well understood that inheritance operates through the replication of DNA sequences and that errors in this process (mutations) and the reshuffling of existing variants (recombination) represent the sources of new variation. In particular, mutations are known to be random (or less confusingly, “undirected”) with respect to any effects that they may have. Any given mutation is merely a chance error in the genetic system, and as such, its likelihood of occurrence is not influenced by whether it will turn out to be detrimental, beneficial, or (most commonly) neutral.

As Darwin anticipated, extensive variation among individuals has now been well established to exist at the physical, physiological, and behavioral levels. Thanks to the rise of molecular biology and, more recently, of genomics, it also has been possible to document variation at the level of proteins, genes, and even individual DNA nucleotides in humans and many other species.

Non-random Differences in Survival and Reproduction

Darwin saw that overproduction and limited resources create a struggle for existence in which some organisms will succeed and most will not. He also recognized that organisms in populations differ from one another in terms of many traits that tend to be passed on from parent to offspring. Darwin's brilliant insight was to combine these two factors and to realize that success in the struggle for existence would not be determined by chance, but instead would be biased by some of the heritable differences that exist among organisms. Specifically, he noted that some individuals happen to possess traits that make them slightly better suited to a particular environment, meaning that they are more likely to survive than individuals with less well suited traits. As a result, organisms with these traits will, on average, leave more offspring than their competitors.

Whereas the origin of a new genetic variant occurs at random in terms of its effects on the organism, the probability of it being passed on to the next generation is absolutely non-random if it impacts the survival and reproductive capabilities of that organism. The important point is that this is a two-step process: first, the origin of variation by random mutation, and second, the non-random sorting of variation due to its effects on survival and reproduction (Mayr 2001 ). Though definitions of natural selection have been phrased in many ways (Table  1 ), it is this non-random difference in survival and reproduction that forms the basis of the process.

Darwinian Fitness

The meaning of fitness in evolutionary biology.

In order to study the operation and effects of natural selection, it is important to have a means of describing and quantifying the relationships between genotype (gene complement), phenotype (physical and behavioral features), survival, and reproduction in particular environments. The concept used by evolutionary biologists in this regard is known as “Darwinian fitness,” which is defined most simply as a measure of the total (or relative) reproductive output of an organism with a particular genotype (Table  1 ). In the most basic terms, one can state that the more offspring an individual produces, the higher is its fitness. It must be emphasized that the term “fitness,” as used in evolutionary biology, does not refer to physical condition, strength, or stamina and therefore differs markedly from its usage in common language.

“Survival of the Fittest” is Misleading

In the fifth edition of the Origin (published in 1869), Darwin began using the phrase “survival of the fittest”, which had been coined a few years earlier by British economist Herbert Spencer, as shorthand for natural selection. This was an unfortunate decision as there are several reasons why “survival of the fittest” is a poor descriptor of natural selection. First, in Darwin's context, “fittest” implied “best suited to a particular environment” rather than “most physically fit,” but this crucial distinction is often overlooked in non-technical usage (especially when further distorted to “only the strong survive”). Second, it places undue emphasis on survival: While it is true that dead organisms do not reproduce, survival is only important evolutionarily insofar as it affects the number of offspring produced. Traits that make life longer or less difficult are evolutionarily irrelevant unless they also influence reproductive output. Indeed, traits that enhance net reproduction may increase in frequency over many generations even if they compromise individual longevity. Conversely, differences in fecundity alone can create differences in fitness, even if survival rates are identical among individuals. Third, this implies an excessive focus on organisms, when in fact traits or their underlying genes equally can be identified as more or less fit than alternatives. Lastly, this phrase is often misconstrued as being circular or tautological (Who survives? The fittest. Who are the fittest? Those who survive). However, again, this misinterprets the modern meaning of fitness, which can be both predicted in terms of which traits are expected to be successful in a specific environment and measured in terms of actual reproductive success in that environment.

Which Traits Are the Most Fit?

Directional natural selection can be understood as a process by which fitter traits (or genes) increase in proportion within populations over the course of many generations. It must be understood that the relative fitness of different traits depends on the current environment. Thus, traits that are fit now may become unfit later if the environment changes. Conversely, traits that have now become fit may have been present long before the current environment arose, without having conferred any advantage under previous conditions. Finally, it must be noted that fitness refers to reproductive success relative to alternatives here and now —natural selection cannot increase the proportion of traits solely because they may someday become advantageous. Careful reflection on how natural selection actually works should make it clear why this is so.

Natural Selection and Adaptive Evolution

Natural selection and the evolution of populations.

Though each has been tested and shown to be accurate, none of the observations and inferences that underlies natural selection is sufficient individually to provide a mechanism for evolutionary change Footnote 6 . Overproduction alone will have no evolutionary consequences if all individuals are identical. Differences among organisms are not relevant unless they can be inherited. Genetic variation by itself will not result in natural selection unless it exerts some impact on organism survival and reproduction. However, any time all of Darwin's postulates hold simultaneously—as they do in most populations—natural selection will occur. The net result in this case is that certain traits (or, more precisely, genetic variants that specify those traits) will, on average , be passed on from one generation to the next at a higher rate than existing alternatives in the population. Put another way, when one considers who the parents of the current generation were, it will be seen that a disproportionate number of them possessed traits beneficial for survival and reproduction in the particular environment in which they lived.

The important points are that this uneven reproductive success among individuals represents a process that occurs in each generation and that its effects are cumulative over the span of many generations. Over time, beneficial traits will become increasingly prevalent in descendant populations by virtue of the fact that parents with those traits consistently leave more offspring than individuals lacking those traits. If this process happens to occur in a consistent direction—say, the largest individuals in each generation tend to leave more offspring than smaller individuals—then there can be a gradual, generation-by-generation change in the proportion of traits in the population. This change in proportion and not the modification of organisms themselves is what leads to changes in the average value of a particular trait in the population. Organisms do not evolve; populations evolve.

The term “adaptation” derives from ad + aptus , literally meaning “toward + fit”. As the name implies, this is the process by which populations of organisms evolve in such a way as to become better suited to their environments as advantageous traits become predominant. On a broader scale, it is also how physical, physiological, and behavioral features that contribute to survival and reproduction (“adaptations”) arise over evolutionary time. This latter topic is particularly difficult for many to grasp, though of course a crucial first step is to understand the operation of natural selection on smaller scales of time and consequence. (For a detailed discussion of the evolution of complex organs such as eyes, see Gregory 2008b .)

On first pass, it may be difficult to see how natural selection can ever lead to the evolution of new characteristics if its primary effect is merely to eliminate unfit traits. Indeed, natural selection by itself is incapable of producing new traits, and in fact (as many readers will have surmised), most forms of natural selection deplete genetic variation within populations. How, then, can an eliminative process like natural selection ever lead to creative outcomes?

To answer this question, one must recall that evolution by natural selection is a two-step process. The first step involves the generation of new variation by mutation and recombination, whereas the second step determines which randomly generated variants will persist into the next generation. Most new mutations are neutral with respect to survival and reproduction and therefore are irrelevant in terms of natural selection (but not, it must be pointed out, to evolution more broadly). The majority of mutations that have an impact on survival and reproductive output will do so negatively and, as such, will be less likely than existing alternatives to be passed on to subsequent generations. However, a small percentage of new mutations will turn out to have beneficial effects in a particular environment and will contribute to an elevated rate of reproduction by organisms possessing them. Even a very slight advantage is sufficient to cause new beneficial mutations to increase in proportion over the span of many generations.

Biologists sometimes describe beneficial mutations as “spreading” or “sweeping” through a population, but this shorthand is misleading. Rather, beneficial mutations simply increase in proportion from one generation to the next because, by definition, they happen to contribute to the survival and reproductive success of the organisms carrying them. Eventually, a beneficial mutation may be the only alternative left as all others have ultimately failed to be passed on. At this point, that beneficial genetic variant is said to have become “fixed” in the population.

Again, mutation does not occur in order to improve fitness—it merely represents errors in genetic replication. This means that most mutations do not improve fitness: There are many more ways of making things worse than of making them better. It also means that mutations will continue to occur even after previous beneficial mutations have become fixed. As such, there can be something of a ratcheting effect in which beneficial mutations arise and become fixed by selection, only to be supplemented later by more beneficial mutations which, in turn, become fixed. All the while, neutral and deleterious mutations also occur in the population, the latter being passed on at a lower rate than alternatives and often being lost before reaching any appreciable frequency.

Of course, this is an oversimplification—in species with sexual reproduction, multiple beneficial mutations may be brought together by recombination such that the fixation of beneficial genes need not occur sequentially. Likewise, recombination can juxtapose deleterious mutations, thereby hastening their loss from the population. Nonetheless, it is useful to imagine the process of adaptation as one in which beneficial mutations arise continually (though perhaps very infrequently and with only minor positive impacts) and then accumulate in the population over many generations.

The process of adaptation in a population is depicted in very basic form in Fig.  2 . Several important points can be drawn from even such an oversimplified rendition:

Mutations are the source of new variation. Natural selection itself does not create new traits; it only changes the proportion of variation that is already present in the population. The repeated two-step interaction of these processes is what leads to the evolution of novel adaptive features.

Mutation is random with respect to fitness. Natural selection is, by definition, non-random with respect to fitness. This means that, overall, it is a serious misconception to consider adaptation as happening “by chance”.

Mutations occur with all three possible outcomes: neutral, deleterious, and beneficial. Beneficial mutations may be rare and deliver only a minor advantage, but these can nonetheless increase in proportion in the population over many generations by natural selection. The occurrence of any particular beneficial mutation may be very improbable, but natural selection is very effective at causing these individually unlikely improvements to accumulate. Natural selection is an improbability concentrator.

No organisms change as the population adapts. Rather, this involves changes in the proportion of beneficial traits across multiple generations.

The direction in which adaptive change occurs is dependent on the environment. A change in environment can make previously beneficial traits neutral or detrimental and vice versa.

Adaptation does not result in optimal characteristics. It is constrained by historical, genetic, and developmental limitations and by trade-offs among features (see Gregory 2008b ).

It does not matter what an “ideal” adaptive feature might be—the only relevant factor is that variants that happen to result in greater survival and reproduction relative to alternative variants are passed on more frequently. As Darwin wrote in a letter to Joseph Hooker (11 Sept. 1857), “I have just been writing an audacious little discussion, to show that organic beings are not perfect, only perfect enough to struggle with their competitors.”

The process of adaptation by natural selection is not forward-looking, and it cannot produce features on the grounds that they might become beneficial sometime in the future. In fact, adaptations are always to the conditions experienced by generations in the past.

A highly simplified depiction of natural selection ( Correct ) and a generalized illustration of various common misconceptions about the mechanism ( Incorrect ). Properly understood, natural selection occurs as follows: ( A ) A population of organisms exhibits variation in a particular trait that is relevant to survival in a given environment. In this diagram, darker coloration happens to be beneficial, but in another environment, the opposite could be true. As a result of their traits, not all individuals in Generation 1 survive equally well, meaning that only a non-random subsample ultimately will succeed in reproducing and passing on their traits ( B ). Note that no individual organisms in Generation 1 change, rather the proportion of individuals with different traits changes in the population. The individuals who survive from Generation 1 reproduce to produce Generation 2. ( C ) Because the trait in question is heritable, this second generation will (mostly) resemble the parent generation. However, mutations have also occurred, which are undirected (i.e., they occur at random in terms of the consequences of changing traits), leading to both lighter and darker offspring in Generation 2 as compared to their parents in Generation 1. In this environment, lighter mutants are less successful and darker mutants are more successful than the parental average. Once again, there is non-random survival among individuals in the population, with darker traits becoming disproportionately common due to the death of lighter individuals ( D ). This subset of Generation 2 proceeds to reproduce. Again, the traits of the survivors are passed on, but there is also undirected mutation leading to both deleterious and beneficial differences among the offspring ( E ). ( F ) This process of undirected mutation and natural selection (non-random differences in survival and reproductive success) occurs over many generations, each time leading to a concentration of the most beneficial traits in the next generation. By Generation N , the population is composed almost entirely of very dark individuals. The population can now be said to have become adapted to the environment in which darker traits are the most successful. This contrasts with the intuitive notion of adaptation held by most students and non-biologists. In the most common version, populations are seen as uniform, with variation being at most an anomalous deviation from the norm ( X ). It is assumed that all members within a single generation change in response to pressures imposed by the environment ( Y ). When these individuals reproduce, they are thought to pass on their acquired traits. Moreover, any changes that do occur due to mutation are imagined to be exclusively in the direction of improvement ( Z ). Studies have revealed that it can be very difficult for non-experts to abandon this intuitive interpretation in favor of a scientifically valid understanding of the mechanism. Diagrams based in part on Bishop and Anderson ( 1990 )

Natural Selection Is Elegant, Logical, and Notoriously Difficult to Grasp

The extent of the problem.

In its most basic form, natural selection is an elegant theory that effectively explains the obviously good fit of living things to their environments. As a mechanism, it is remarkably simple in principle yet incredibly powerful in application. However, the fact that it eluded description until 150 years ago suggests that grasping its workings and implications is far more challenging than is usually assumed.

Three decades of research have produced unambiguous data revealing a strikingly high prevalence of misconceptions about natural selection among members of the public and in students at all levels, from elementary school pupils to university science majors (Alters 2005 ; Bardapurkar 2008 ; Table  2 ) Footnote 7 . A finding that less than 10% of those surveyed possess a functional understanding of natural selection is not atypical. It is particularly disconcerting and undoubtedly exacerbating that confusions about natural selection are common even among those responsible for teaching it Footnote 8 . As Nehm and Schonfeld ( 2007 ) recently concluded, “one cannot assume that biology teachers with extensive backgrounds in biology have an accurate working knowledge of evolution, natural selection, or the nature of science.”

Why is Natural Selection so Difficult to Understand?

Two obvious hypotheses present themselves for why misunderstandings of natural selection are so widespread. The first is that understanding the mechanism of natural selection requires an acceptance of the historical fact of evolution, the latter being rejected by a large fraction of the population. While an improved understanding of the process probably would help to increase overall acceptance of evolution, surveys indicate that rates of acceptance already are much higher than levels of understanding. And, whereas levels of understanding and acceptance may be positively correlated among teachers (Vlaardingerbroek and Roederer 1997 ; Rutledge and Mitchell 2002 ; Deniz et al. 2008 ), the two parameters seem to be at most only very weakly related in students Footnote 9 (Bishop and Anderson 1990 ; Demastes et al. 1995 ; Brem et al. 2003 ; Sinatra et al. 2003 ; Ingram and Nelson 2006 ; Shtulman 2006 ). Teachers notwithstanding, “it appears that a majority on both sides of the evolution-creation debate do not understand the process of natural selection or its role in evolution” (Bishop and Anderson 1990 ).

The second intuitive hypothesis is that most people simply lack formal education in biology and have learned incorrect versions of evolutionary mechanisms from non-authoritative sources (e.g., television, movies, parents). Inaccurate portrayals of evolutionary processes in the media, by teachers, and by scientists themselves surely exacerbate the situation (e.g., Jungwirth 1975a , b , 1977 ; Moore et al. 2002 ). However, this alone cannot provide a full explanation, because even direct instruction on natural selection tends to produce only modest improvements in students' understanding (e.g., Jensen and Finley 1995 ; Ferrari and Chi 1998 ; Nehm and Reilly 2007 ; Spindler and Doherty 2009 ). There also is evidence that levels of understanding do not differ greatly between science majors and non-science majors (Sundberg and Dini 1993 ). In the disquieting words of Ferrari and Chi ( 1998 ), “misconceptions about even the basic principles of Darwin's theory of evolution are extremely robust, even after years of education in biology.”

Misconceptions are well known to be common with many (perhaps most) aspects of science, including much simpler and more commonly encountered phenomena such as the physics of motion (e.g., McCloskey et al. 1980 ; Halloun and Hestenes 1985 ; Bloom and Weisberg 2007 ). The source of this larger problem seems to be a significant disconnect between the nature of the world as reflected in everyday experience and the one revealed by systematic scientific investigation (e.g., Shtulman 2006 ; Sinatra et al. 2008 ). Intuitive interpretations of the world, though sufficient for navigating daily life, are usually fundamentally at odds with scientific principles. If common sense were more than superficially accurate, scientific explanations would be less counterintuitive, but they also would be largely unnecessary.

Conceptual Frameworks Versus Spontaneous Constructions

It has been suggested by some authors that young students simply are incapable of understanding natural selection because they have not yet developed the formal reasoning abilities necessary to grasp it (Lawson and Thompson 1988 ). This could be taken to imply that natural selection should not be taught until later grades; however, those who have studied student understanding directly tend to disagree with any such suggestion (e.g., Clough and Wood-Robinson 1985 ; Settlage 1994 ). Overall, the issue does not seem to be a lack of logic (Greene 1990 ; Settlage 1994 ), but a combination of incorrect underlying premises about mechanisms and deep-seated cognitive biases that influence interpretations.

Many of the misconceptions that block an understanding of natural selection develop early in childhood as part of “naïve” but practical understandings of how the world is structured. These tend to persist unless replaced with more accurate and equally functional information. In this regard, some experts have argued that the goal of education should be to supplant existing conceptual frameworks with more accurate ones (see Sinatra et al. 2008 ). Under this view, “Helping people to understand evolution...is not a matter of adding on to their existing knowledge, but helping them to revise their previous models of the world to create an entirely new way of seeing” (Sinatra et al. 2008 ). Other authors suggest that students do not actually maintain coherent conceptual frameworks relating to complex phenomena, but instead construct explanations spontaneously using intuitions derived from everyday experience (see Southerland et al. 2001 ). Though less widely accepted, this latter view gains support from the observation that naïve evolutionary explanations given by non-experts may be tentative and inconsistent (Southerland et al. 2001 ) and may differ depending on the type of organisms being considered (Spiegel et al. 2006 ). In some cases, students may attempt a more complex explanation but resort to intuitive ideas when they encounter difficulty (Deadman and Kelly 1978 ). In either case, it is abundantly clear that simply describing the process of natural selection to students is ineffective and that it is imperative that misconceptions be confronted if they are to be corrected (e.g., Greene 1990 ; Scharmann 1990 ; Settlage 1994 ; Ferrari and Chi 1998 ; Alters and Nelson 2002 ; Passmore and Stewart 2002 ; Alters 2005 ; Nelson 2007 ).

A Catalog of Common Misconceptions

Whereas the causes of cognitive barriers to understanding remain to be determined, their consequences are well documented. It is clear from many studies that complex but accurate explanations of biological adaptation typically yield to naïve intuitions based on common experience (Fig.  2 ; Tables  2 and 3 ). As a result, each of the fundamental components of natural selection may be overlooked or misunderstood when it comes time to consider them in combination, even if individually they appear relatively straightforward. The following sections provide an overview of the various, non-mutually exclusive, and often correlated misconceptions that have been found to be most common. All readers are encouraged to consider these conceptual pitfalls carefully in order that they may be avoided. Teachers, in particular, are urged to familiarize themselves with these errors so that they may identify and address them among their students.

Teleology and the “Function Compunction”

Much of the human experience involves overcoming obstacles, achieving goals, and fulfilling needs. Not surprisingly, human psychology includes a powerful bias toward thoughts about the “purpose” or “function” of objects and behaviors—what Kelemen and Rosset ( 2009 ) dub the “human function compunction.” This bias is particularly strong in children, who are apt to see most of the world in terms of purpose; for example, even suggesting that “rocks are pointy to keep animals from sitting on them” (Kelemen 1999a , b ; Kelemen and Rosset 2009 ). This tendency toward explanations based on purpose (“teleology”) runs very deep and persists throughout high school (Southerland et al. 2001 ) and even into postsecondary education (Kelemen and Rosset 2009 ). In fact, it has been argued that the default mode of teleological thinking is, at best, suppressed rather than supplanted by introductory scientific education. It therefore reappears easily even in those with some basic scientific training; for example, in descriptions of ecological balance (“fungi grow in forests to help decomposition”) or species survival (“finches diversified in order to survive”; Kelemen and Rosset 2009 ).

Teleological explanations for biological features date back to Aristotle and remain very common in naïve interpretations of adaptation (e.g., Tamir and Zohar 1991 ; Pedersen and Halldén 1992 ; Southerland et al. 2001 ; Sinatra et al. 2008 ; Table  2 ). On the one hand, teleological reasoning may preclude any consideration of mechanisms altogether if simply identifying a current function for an organ or behavior is taken as sufficient to explain its existence (e.g., Bishop and Anderson 1990 ). On the other hand, when mechanisms are considered by teleologically oriented thinkers, they are often framed in terms of change occurring in response to a particular need (Table  2 ). Obviously, this contrasts starkly with a two-step process involving undirected mutations followed by natural selection (see Fig.  2 and Table  3 ).

Anthropomorphism and Intentionality

A related conceptual bias to teleology is anthropomorphism, in which human-like conscious intent is ascribed either to the objects of natural selection or to the process itself (see below). In this sense, anthropomorphic misconceptions can be characterized as either internal (attributing adaptive change to the intentional actions of organisms) or external (conceiving of natural selection or “Nature” as a conscious agent; e.g., Kampourakis and Zogza 2008 ; Sinatra et al. 2008 ).

Internal anthropomorphism or “intentionality” is intimately tied to the misconception that individual organisms evolve in response to challenges imposed by the environment (rather than recognizing evolution as a population-level process). Gould ( 1980 ) described the obvious appeal of such intuitive notions as follows:

Since the living world is a product of evolution, why not suppose that it arose in the simplest and most direct way? Why not argue that organisms improve themselves by their own efforts and pass these advantages to their offspring in the form of altered genes—a process that has long been called, in technical parlance, the “inheritance of acquired characters.” This idea appeals to common sense not only for its simplicity but perhaps even more for its happy implication that evolution travels an inherently progressive path, propelled by the hard work of organisms themselves.

The penchant for seeing conscious intent is often sufficiently strong that it is applied not only to non-human vertebrates (in which consciousness, though certainly not knowledge of genetics and Darwinian fitness, may actually occur), but also to plants and even to single-celled organisms. Thus, adaptations in any taxon may be described as “innovations,” “inventions,” or “solutions” (sometimes “ingenious” ones, no less). Even the evolution of antibiotic resistance is characterized as a process whereby bacteria “learn” to “outsmart” antibiotics with frustrating regularity. Anthropomorphism with an emphasis on forethought is also behind the common misconception that organisms behave as they do in order to enhance the long-term well-being of their species. Once again, a consideration of the actual mechanics of natural selection should reveal why this is fallacious.

All too often, an anthropomorphic view of evolution is reinforced with sloppy descriptions by trusted authorities (Jungwirth 1975a , b , 1977 ; Moore et al. 2002 ). Consider this particularly egregious example from a website maintained by the National Institutes of Health Footnote 10 :

As microbes evolve, they adapt to their environment. If something stops them from growing and spreading—such as an antimicrobial—they evolve new mechanisms to resist the antimicrobials by changing their genetic structure. Changing the genetic structure ensures that the offspring of the resistant microbes are also resistant.

Fundamentally inaccurate descriptions such as this are alarmingly common. As a corrective, it is a useful exercise to translate such faulty characterizations into accurate language Footnote 11 . For example, this could read:

Bacteria that cause disease exist in large populations, and not all individuals are alike. If some individuals happen to possess genetic features that make them resistant to antibiotics, these individuals will survive the treatment while the rest gradually are killed off. As a result of their greater survival, the resistant individuals will leave more offspring than susceptible individuals, such that the proportion of resistant individuals will increase each time a new generation is produced. When only the descendants of the resistant individuals are left, the population of bacteria can be said to have evolved resistance to the antibiotics.

Use and Disuse

Many students who manage to avoid teleological and anthropomorphic pitfalls nonetheless conceive of evolution as involving change due to use or disuse of organs. This view, which was developed explicitly by Jean-Baptiste Lamarck but was also invoked to an extent by Darwin ( 1859 ), emphasizes changes to individual organisms that occur as they use particular features more or less. For example, Darwin ( 1859 ) invoked natural selection to explain the loss of sight in some subterranean rodents, but instead favored disuse alone as the explanation for loss of eyes in blind, cave-dwelling animals: “As it is difficult to imagine that eyes, though useless, could be in any way injurious to animals living in darkness, I attribute their loss wholly to disuse.” This sort of intuition remains common in naïve explanations for why unnecessary organs become vestigial or eventually disappear. Modern evolutionary theory recognizes several reasons that may account for the loss of complex features (e.g., Jeffery 2005 ; Espinasa and Espinasa 2008 ), some of which involve direct natural selection, but none of which is based simply on disuse.

Soft Inheritance

Evolution involving changes in individual organisms, whether based on conscious choice or use and disuse, would require that characteristics acquired during the lifetime of an individual be passed on to offspring Footnote 12 , a process often termed “soft inheritance.” The notion that acquired traits can be transmitted to offspring remained a common assumption among thinkers for more than 2,000 years, including into Darwin's time (Zirkle 1946 ). As is now understood, inheritance is actually “hard,” meaning that physical changes that occur during an organism's lifetime are not passed to offspring. This is because the cells that are involved in reproduction (the germline) are distinct from those that make up the rest of the body (the somatic line); only changes that affect the germline can be passed on. New genetic variants arise through mutation and recombination during replication and will often only exert their effects in offspring and not in the parents in whose reproductive cells they occur (though they could also arise very early in development and appear later in the adult offspring). Correct and incorrect interpretations of inheritance are contrasted in Fig.  3 .

A summary of correct ( left ) and incorrect ( right ) conceptions of heredity as it pertains to adaptive evolutionary change. The panels on the left display the operation of “hard inheritance”, whereas those on the right illustrate naïve mechanisms of “soft inheritance”. In all diagrams, a set of nine squares represents an individual multicellular organism and each square represents a type of cell of which the organisms are constructed. In the left panels, the organisms include two kinds of cells: those that produce gametes (the germline, black ) and those that make up the rest of the body (the somatic line, white ). In the top left panel , all cells in a parent organism initially contain a gene that specifies white coloration marked W ( A ). A random mutation occurs in the germline, changing the gene from one that specifies white to one that specifies gray marked G ( B ). This mutant gene is passed to the egg ( C ), which then develops into an offspring exhibiting gray coloration ( D ). The mutation in this case occurred in the parent (specifically, in the germline) but its effects did not become apparent until the next generation. In the bottom left panel , a parent once again begins with white coloration and the white gene in all of its cells ( H ). During its lifetime, the parent comes to acquire a gray coloration due to exposure to particular environmental conditions ( I ). However, because this does not involve any change to the genes in the germline, the original white gene is passed into the egg ( J ), and the offspring exhibits none of the gray coloration that was acquired by its parent ( K ). In the top right panel , the distinction between germline and somatic line is not understood. In this case, a parent that initially exhibits white coloration ( P ) changes during its lifetime to become gray ( Q ). Under incorrect views of soft inheritance, this altered coloration is passed on to the egg ( R ), and the offspring is born with the gray color acquired by its parent ( S ). In the bottom right panel , a more sophisticated but still incorrect view of inheritance is shown. Here, traits are understood to be specified by genes, but no distinction is recognized between the germline and somatic line. In this situation, a parent begins with white coloration and white-specifying genes in all its cells ( W ). A mutation occurs in one type of body cells to change those cells to gray ( X ). A mixture of white and gray genes is passed on to the egg ( Y ), and the offspring develops white coloration in most cells but gray coloration in the cells where gray-inducing mutations arose in the parent ( Z ). Intuitive ideas regarding soft inheritance underlie many misconceptions of how adaptive evolution takes place (see Fig.  2 )

Studies have indicated that belief in soft inheritance arises early in youth as part of a naïve model of heredity (e.g., Deadman and Kelly 1978 ; Kargbo et al. 1980 ; Lawson and Thompson 1988 ; Wood-Robinson 1994 ). That it seems intuitive probably explains why the idea of soft inheritance persisted so long among prominent thinkers and why it is so resistant to correction among modern students. Unfortunately, a failure to abandon this belief is fundamentally incompatible with an appreciation of evolution by natural selection as a two-step process in which the origin of new variation and its relevance to survival in a particular environment are independent considerations.

Nature as a Selecting Agent

Thirty years ago, widely respected broadcaster Sir David Attenborough ( 1979 ) aptly described the challenge of avoiding anthropomorphic shorthand in descriptions of adaptation:

Darwin demonstrated that the driving force of [adaptive] evolution comes from the accumulation, over countless generations, of chance genetical changes sifted by the rigors of natural selection. In describing the consequences of this process it is only too easy to use a form of words that suggests that the animals themselves were striving to bring about change in a purposeful way–that fish wanted to climb onto dry land, and to modify their fins into legs, that reptiles wished to fly, strove to change their scales into feathers and so ultimately became birds.

Unlike many authors, Attenborough ( 1979 ) admirably endeavored to not use such misleading terminology. However, this quote inadvertently highlights an additional challenge in describing natural selection without loaded language. In it, natural selection is described as a “driving force” that rigorously “sifts” genetic variation, which could be misunderstood to imply that it takes an active role in prompting evolutionary change. Much more seriously, one often encounters descriptions of natural selection as a processes that “chooses” among “preferred” variants or “experiments with” or “explores” different options. Some expressions, such as “favored” and “selected for” are used commonly as shorthand in evolutionary biology and are not meant to impart consciousness to natural selection; however, these too may be misinterpreted in the vernacular sense by non-experts and must be clarified.

Darwin ( 1859 ) himself could not resist slipping into the language of agency at times:

It may be said that natural selection is daily and hourly scrutinizing, throughout the world, every variation, even the slightest; rejecting that which is bad, preserving and adding up all that is good; silently and insensibly working, whenever and wherever opportunity offers, at the improvement of each organic being in relation to its organic and inorganic conditions of life. We see nothing of these slow changes in progress, until the hand of time has marked the long lapse of ages, and then so imperfect is our view into long past geological ages, that we only see that the forms of life are now different from what they formerly were.

Perhaps recognizing the ease with which such language can be misconstrued, Darwin ( 1868 ) later wrote that “The term ‘Natural Selection’ is in some respects a bad one, as it seems to imply conscious choice; but this will be disregarded after a little familiarity.” Unfortunately, more than “a little familiarity” seems necessary to abandon the notion of Nature as an active decision maker.

Being, as it is, the simple outcome of differences in reproductive success due to heritable traits, natural selection cannot have plans, goals, or intentions, nor can it cause changes in response to need. For this reason, Jungwirth ( 1975a , b , 1977 ) bemoaned the tendency for authors and instructors to invoke teleological and anthropomorphic descriptions of the process and argued that this served to reinforce misconceptions among students (see also Bishop and Anderson 1990 ; Alters and Nelson 2002 ; Moore et al. 2002 ; Sinatra et al. 2008 ). That said, a study of high school students by Tamir and Zohar ( 1991 ) suggested that older students can recognize the distinction between an anthropomorphic or teleological formulation (i.e., merely a convenient description) versus an anthropomorphic/teleological explanation (i.e., involving conscious intent or goal-oriented mechanisms as causal factors; see also Bartov 1978 , 1981 ). Moore et al. ( 2002 ), by contrast, concluded from their study of undergraduates that “students fail to distinguish between the relatively concrete register of genetics and the more figurative language of the specialist shorthand needed to condense the long view of evolutionary processes” (see also Jungwirth 1975a , 1977 ). Some authors have argued that teleological wording can have some value as shorthand for describing complex phenomena in a simple way precisely because it corresponds to normal thinking patterns, and that contrasting this explicitly with accurate language can be a useful exercise during instruction (Zohar and Ginossar 1998 ). In any case, biologists and instructors should be cognizant of the risk that linguistic shortcuts may send students off track.

Source Versus Sorting of Variation

Intuitive models of evolution based on soft inheritance are one-step models of adaptation: Traits are modified in one generation and appear in their altered form in the next. This is in conflict with the actual two-step process of adaptation involving the independent processes of mutation and natural selection. Unfortunately, many students who eschew soft inheritance nevertheless fail to distinguish natural selection from the origin of new variation (e.g., Greene 1990 ; Creedy 1993 ; Moore et al. 2002 ). Whereas an accurate understanding recognizes that most new mutations are neutral or harmful in a given environment, such naïve interpretations assume that mutations occur as a response to environmental challenges and therefore are always beneficial (Fig.  2 ). For example, many students may believe that exposure to antibiotics directly causes bacteria to become resistant, rather than simply changing the relative frequencies of resistant versus non-resistant individuals by killing off the latter Footnote 13 . Again, natural selection itself does not create new variation, it merely influences the proportion of existing variants. Most forms of selection reduce the amount of genetic variation within populations, which may be counteracted by the continual emergence of new variation via undirected mutation and recombination.

Typological, Essentialist, and Transformationist Thinking

Misunderstandings about how variation arises are problematic, but a common failure to recognize that it plays a role at all represents an even a deeper concern. Since Darwin ( 1859 ), evolutionary theory has been based strongly on “population” thinking that emphasizes differences among individuals. By contrast, many naïve interpretations of evolution remain rooted in the “typological” or “essentialist” thinking that has existed since the ancient Greeks (Mayr 1982 , 2001 ; Sinatra et al. 2008 ). In this case, species are conceived of as exhibiting a single “type” or a common “essence,” with variation among individuals representing anomalous and largely unimportant deviations from the type or essence. As Shtulman ( 2006 ) notes, “human beings tend to essentialize biological kinds and essentialism is incompatible with natural selection.” As with many other conceptual biases, the tendency to essentialize seems to arise early in childhood and remains the default for most individuals (Strevens 2000 ; Gelman 2004 ; Evans et al. 2005 ; Shtulman 2006 ).

The incorrect belief that species are uniform leads to “transformationist” views of adaptation in which an entire population transforms as a whole as it adapts (Alters 2005 ; Shtulman 2006 ; Bardapurkar 2008 ). This contrasts with the correct, “variational” understanding of natural selection in which it is the proportion of traits within populations that changes (Fig.  2 ). Not surprisingly, transformationist models of adaptation usually include a tacit assumption of soft inheritance and one-step change in response to challenges. Indeed, Shtulman ( 2006 ) found that transformationists appeal to “need” as a cause of evolutionary change three times more often than do variationists.

Events and Absolutes Versus Processes and Probabilities

A proper understanding of natural selection recognizes it as a process that occurs within populations over the course of many generations. It does so through cumulative, statistical effects on the proportion of traits differing in their consequences for reproductive success. This contrasts with two major errors that are commonly incorporated into naïve conceptions of the process:

Natural selection is mistakenly seen as an event rather than as a process (Ferrari and Chi 1998 ; Sinatra et al. 2008 ). Events generally have a beginning and end, occur in a specific sequential order, consist of distinct actions, and may be goal-oriented. By contrast, natural selection actually occurs continually and simultaneously within entire populations and is not goal-oriented (Ferrari and Chi 1998 ). Misconstruing selection as an event may contribute to transformationist thinking as adaptive changes are thought to occur in the entire population simultaneously. Viewing natural selection as a single event can also lead to incorrect “saltationist” assumptions in which complex adaptive features are imagined to appear suddenly in a single generation (see Gregory 2008b for an overview of the evolution of complex organs).

Natural selection is incorrectly conceived as being “all or nothing,” with all unfit individuals dying and all fit individuals surviving. In actuality, it is a probabilistic process in which some traits make it more likely—but do not guarantee—that organisms possessing them will successfully reproduce. Moreover, the statistical nature of the process is such that even a small difference in reproductive success (say, 1%) is enough to produce a gradual increase in the frequency of a trait over many generations.

Concluding Remarks

Surveys of students at all levels paint a bleak picture regarding the level of understanding of natural selection. Though it is based on well-established and individually straightforward components, a proper grasp of the mechanism and its implications remains very rare among non-specialists. The unavoidable conclusion is that the vast majority of individuals, including most with postsecondary education in science, lack a basic understanding of how adaptive evolution occurs.

While no concrete solutions to this problem have yet been found, it is evident that simply outlining the various components of natural selection rarely imparts an understanding of the process to students. Various alternative teaching strategies and activities have been suggested, and some do help to improve the level of understanding among students (e.g., Bishop and Anderson 1986 ; Jensen and Finley 1995 , 1996 ; Firenze 1997 ; Passmore and Stewart 2002 ; Sundberg 2003 ; Alters 2005 ; Scharmann 1990 ; Wilson 2005 ; Nelson 2007 , 2008 ; Pennock 2007 ; Kampourakis and Zogza 2008 ). Efforts to integrate evolution throughout biology curricula rather than segregating it into a single unit may also prove more effective (Nehm et al. 2009 ), as may steps taken to make evolution relevant to everyday concerns (e.g., Hillis 2007 ).

At the very least, it is abundantly clear that teaching and learning natural selection must include efforts to identify, confront, and supplant misconceptions. Most of these derive from deeply held conceptual biases that may have been present since childhood. Natural selection, like most complex scientific theories, runs counter to common experience and therefore competes—usually unsuccessfully—with intuitive ideas about inheritance, variation, function, intentionality, and probability. The tendency, both outside and within academic settings, to use inaccurate language to describe evolutionary phenomena probably serves to reinforce these problems.

Natural selection is a central component of modern evolutionary theory, which in turn is the unifying theme of all biology. Without a grasp of this process and its consequences, it is simply impossible to understand, even in basic terms, how and why life has become so marvelously diverse. The enormous challenge faced by biologists and educators in correcting the widespread misunderstanding of natural selection is matched only by the importance of the task.

For a more advanced treatment, see Bell ( 1997 , 2008 ) or consult any of the major undergraduate-level evolutionary biology or population genetics textbooks.

The Origin was, in Darwin's words, an “abstract” of a much larger work he had initially intended to write. Much of the additional material is available in Darwin ( 1868 ) and Stauffer ( 1975 ).

See Gregory ( 2008a ) for a discussion regarding the use of the term “theory” in science.

Ridley ( 2004 ) points out that Darwin's calculations require overlapping generations to reach this exact number, but the point remains that even in slow-reproducing species the rate of potential production is enormous relative to actual numbers of organisms.

Humans are currently undergoing a rapid population expansion, but this is the exception rather than the rule. As Darwin ( 1859 ) noted, “Although some species may now be increasing, more or less rapidly, in numbers, all cannot do so, for the world would not hold them.”

It cannot be overemphasized that “evolution” and “natural selection” are not interchangeable. This is because not all evolution occurs by natural selection and because not all outcomes of natural selection involve changes in the genetic makeup of populations. A detailed discussion of the different types of selection is beyond the scope of this article, but it can be pointed out that the effect of “stabilizing selection” is to prevent directional change in populations.

Instructors interested in assessing their own students' level of understanding may wish to consult tests developed by Bishop and Anderson ( 1986 ), Anderson et al. ( 2002 ), Beardsley ( 2004 ), Shtulman ( 2006 ), or Kampourakis and Zogza ( 2009 ).

Even more alarming is a recent indication that one in six teachers in the USA is a young Earth creationist, and that about one in eight teaches creationism as though it were a valid alternative to evolutionary science (Berkman et al. 2008 ).

Strictly speaking, it is not necessary to understand how evolution occurs to be convinced that it has occurred because the historical fact of evolution is supported by many convergent lines of evidence that are independent of discussions about particular mechanisms. Again, this represents the important distinction between evolution as fact and theory. See Gregory ( 2008a ).

http://www3.niaid.nih.gov/topics/antimicrobialResistance/Understanding/history.htm , accessed February 2009.

One should always be wary of the linguistic symptoms of anthropomorphic misconceptions, which usually include phrasing like “so that” (versus “because”) or “in order to” (versus “happened to”) when explaining adaptations (Kampourakis and Zogza 2009 ).

It must be noted that the persistent tendency to label the inheritance of acquired characteristics as “Lamarckian” is false: Soft inheritance was commonly accepted long before Lamarck's time (Zirkle 1946 ). Likewise, mechanisms involving organisms' conscious desires to change are often incorrectly attributed to Lamarck. For recent critiques of the tendency to describe various misconceptions as Lamarckian, see Geraedts and Boersma ( 2006 ) and Kampourakis and Zogza ( 2007 ). It is unfortunate that these mistakenly attributed concepts serve as the primary legacy of Lamarck, who in actuality made several important contributions to biology (a term first used by Lamarck), including greatly advancing the classification of invertebrates (another term he coined) and, of course, developing the first (albeit ultimately incorrect) mechanistic theory of evolution. For discussions of Lamarck's views and contributions to evolutionary biology, see Packard ( 1901 ), Burkhardt ( 1972 , 1995 ), Corsi ( 1988 ), Humphreys ( 1995 , 1996 ), and Kampourakis and Zogza ( 2007 ). Lamarck's works are available online at http://www.lamarck.cnrs.fr/index.php?lang=en .

One may wonder how this misconception is reconciled with the common admonition by medical doctors to complete each course of treatment with antibiotics even after symptoms disappear—would this not provide more opportunities for bacteria to “develop” resistance by prolonging exposure?

Alters B. Teaching biological evolution in higher education. Boston: Jones and Bartlett; 2005.

Google Scholar  

Alters BJ, Nelson CE. Teaching evolution in higher education. Evolution. 2002;56:1891–901.

Anderson DL, Fisher KM, Norman GJ. Development and evaluation of the conceptual inventory of natural selection. J Res Sci Teach. 2002;39:952–78. doi: 10.1002/tea.10053 .

Asghar A, Wiles JR, Alters B. Canadian pre-service elementary teachers' conceptions of biological evolution and evolution education. McGill J Educ. 2007;42:189–209.

Attenborough D. Life on earth. Boston: Little, Brown and Company; 1979.

Banet E, Ayuso GE. Teaching of biological inheritance and evolution of living beings in secondary school. Int J Sci Edu 2003;25:373–407.

Bardapurkar A. Do students see the “selection” in organic evolution? A critical review of the causal structure of student explanations. Evo Edu Outreach. 2008;1:299–305. doi: 10.1007/s12052-008-0048-5 .

Barton NH, Briggs DEG, Eisen JA, Goldstein DB, Patel NH. Evolution. Cold Spring Harbor: Cold Spring Harbor Laboratory Press; 2007.

Bartov H. Can students be taught to distinguish between teleological and causal explanations? J Res Sci Teach. 1978;15:567–72. doi: 10.1002/tea.3660150619 .

Bartov H. Teaching students to understand the advantages and disadvantages of teleological and anthropomorphic statements in biology. J Res Sci Teach. 1981;18:79–86. doi: 10.1002/tea.3660180113 .

Beardsley PM. Middle school student learning in evolution: are current standards achievable? Am Biol Teach. 2004;66:604–12. doi: 10.1662/0002-7685(2004)066[0604:MSSLIE]2.0.CO;2 .

Bell G. The basics of selection. New York: Chapman & Hall; 1997.

Bell G. Selection: the mechanism of evolution. 2nd ed. Oxford: Oxford University Press; 2008.

Berkman MB, Pacheco JS, Plutzer E. Evolution and creationism in America's classrooms: a national portrait. PLoS Biol. 2008;6:e124. doi: 10.1371/journal.pbio.0060124 .

Bishop BA, Anderson CW. Evolution by natural selection: a teaching module (Occasional Paper No. 91). East Lansing: Institute for Research on Teaching; 1986.

Bishop BA, Anderson CW. Student conceptions of natural selection and its role in evolution. J Res Sci Teach. 1990;27:415–27. doi: 10.1002/tea.3660270503 .

Bizzo NMV. From Down House landlord to Brazilian high school students: what has happened to evolutionary knowledge on the way? J Res Sci Teach. 1994;31:537–56.

Bloom P, Weisberg DS. Childhood origins of adult resistance to science. Science. 2007;316:996–7. doi: 10.1126/science.1133398 .

CAS   Google Scholar  

Brem SK, Ranney M, Schindel J. Perceived consequences of evolution: college students perceive negative personal and social impact in evolutionary theory. Sci Educ. 2003;87:181–206. doi: 10.1002/sce.10105 .

Brumby M. Problems in learning the concept of natural selection. J Biol Educ. 1979;13:119–22.

Brumby MN. Misconceptions about the concept of natural selection by medical biology students. Sci Educ. 1984;68:493–503. doi: 10.1002/sce.3730680412 .

Burkhardt RW. The inspiration of Lamarck's belief in evolution. J Hist Biol. 1972;5:413–38. doi: 10.1007/BF00346666 .

Burkhardt RW. The spirit of system. Cambridge: Harvard University Press; 1995.

Chinsamy A, Plaganyi E. Accepting evolution. Evolution. 2007;62:248–54.

Clough EE, Wood-Robinson C. How secondary students interpret instances of biological adaptation. J Biol Educ. 1985;19:125–30.

Corsi P. The age of Lamarck. Berkeley: University of California Press; 1988.

Coyne JA. Selling Darwin. Nature. 2006;442:983–4. doi: 10.1038/442983a .

Creedy LJ. Student understanding of natural selection. Res Sci Educ. 1993;23:34–41. doi: 10.1007/BF02357042 .

Curry A. Creationist beliefs persist in Europe. Science. 2009;323:1159. doi: 10.1126/science.323.5918.1159 .

Darimont CT, Carlson SM, Kinnison MT, Paquet PC, Reimchen TE, Wilmers CC. Human predators outpace other agents of trait change in the wild. Proc Natl Acad Sci U S A. 2009;106:952–4. doi: 10.1073/pnas.0809235106 .

Darwin C. On the origin of species by means of natural selection, or the preservation of favoured races in the struggle for life. London: John Murray; 1859.

Darwin, C. The variation of animals and plants under domestication. London: John Murray; 1868.

Darwin C, Wallace AR. On the tendency of species to form varieties; and on the perpetuation of varieties and species by natural means of selection. Proc Linn Soc. 1858;3:46–62.

Deadman JA, Kelly PJ. What do secondary school boys understand about evolution and heredity before they are taught the topic? J Biol Educ. 1978;12:7–15.

Demastes SS, Settlage J, Good R. Students' conceptions of natural selection and its role in evolution: cases of replication and comparison. J Res Sci Teach. 1995;32:535–50. doi: 10.1002/tea.3660320509 .

Deniz H, Donelly LA, Yilmaz I. Exploring the factors related to acceptance of evolutionary theory among Turkish preservice biology teachers: toward a more informative conceptual ecology for biological evolution. J Res Sci Teach. 2008;45:420–43. doi: 10.1002/tea.20223 .

Dennett DC. Darwin's dangerous idea. New York: Touchstone Books; 1995.

Espinasa M, Espinasa L. Losing sight of regressive evolution. Evo Edu Outreach. 2008;1:509–16. doi: 10.1007/s12052-008-0094-z .

Evans EM, Mull MS, Poling DA, Szymanowski K. Overcoming an essentialist bias: from metamorphosis to evolution. In Biennial meeting of the Society for Research in Child Development , Atlanta, GA; 2005.

Evans EM, Spiegel A, Gram W, Frazier BF, Thompson S, Tare M, Diamond J. A conceptual guide to museum visitors’ understanding of evolution. In Annual Meeting of the American Education Research Association , San Francisco; 2006.

Ferrari M, Chi MTH. The nature of naive explanations of natural selection. Int J Sci Educ. 1998;20:1231–56. doi: 10.1080/0950069980201005 .

Firenze R. Lamarck vs. Darwin: dueling theories. Rep Natl Cent Sci Educ. 1997;17:9–11.

Freeman S, Herron JC. Evolutionary analysis. 4th ed. Upper Saddle River: Prentice Hall; 2007.

Futuyma DJ. Evolution. Sunderland: Sinauer; 2005.

Gelman SA. Psychological essentialism in children. Trends Cogn Sci. 2004;8:404–9. doi: 10.1016/j.tics.2004.07.001 .

Geraedts CL, Boersma KT. Reinventing natural selection. Int J Sci Educ. 2006;28:843–70. doi: 10.1080/09500690500404722 .

Gould SJ. Shades of Lamarck. In: The Panda's Thumb. New York: Norton; 1980. p. 76–84.

Greene ED. The logic of university students' misunderstanding of natural selection. J Res Sci Teach. 1990;27:875–85. doi: 10.1002/tea.3660270907 .

Gregory TR. Evolution as fact, theory, and path. Evo Edu Outreach. 2008a;1:46–52. doi: 10.1007/s12052-007-0001-z .

Gregory TR. The evolution of complex organs. Evo Edu Outreach. 2008b;1:358–89. doi: 10.1007/s12052-008-0076-1 .

Gregory TR. Artificial selection and domestication: modern lessons from Darwin's enduring analogy. Evo Edu Outreach. 2009;2:5–27. doi: 10.1007/s12052-008-0114-z .

Hall BK, Hallgrimsson B. Strickberger's evolution. 4th ed. Sudbury: Jones and Bartlett; 2008.

Halldén O. The evolution of the species: pupil perspectives and school perspectives. Int J Sci Educ. 1988;10:541–52. doi: 10.1080/0950069880100507 .

Halloun IA, Hestenes D. The initial knowledge state of college physics students. Am J Phys. 1985;53:1043–55. doi: 10.1119/1.14030 .

Hillis DM. Making evolution relevant and exciting to biology students. Evolution. 2007;61:1261–4. doi: 10.1111/j.1558-5646.2007.00126.x .

Humphreys J. The laws of Lamarck. Biologist. 1995;42:121–5.

Humphreys J. Lamarck and the general theory of evolution. J Biol Educ. 1996;30:295–303.

Ingram EL, Nelson CE. Relationship between achievement and students' acceptance of evolution or creation in an upper-level evolution course. J Res Sci Teach. 2006;43:7–24. doi: 10.1002/tea.20093 .

Jeffery WR. Adaptive evolution of eye degeneration in the Mexican blind cavefish. J Heredity. 2005;96:185–96. doi: 10.1093/jhered/esi028 .

Jensen MS, Finley FN. Teaching evolution using historical arguments in a conceptual change strategy. Sci Educ. 1995;79:147–66. doi: 10.1002/sce.3730790203 .

Jensen MS, Finley FN. Changes in students' understanding of evolution resulting from different curricular and instructional strategies. J Res Sci Teach. 1996;33:879–900. doi: 10.1002/(SICI)1098-2736(199610)33:8<879::AID-TEA4>3.0.CO;2-T .

Jiménez-Aleixandre MP. Thinking about theories or thinking with theories?: a classroom study with natural selection. Int J Sci Educ. 1992;14:51–61. doi: 10.1080/0950069920140106 .

Jiménez-Aleixandre MP, Fernández-Pérez J. Selection or adjustment? Explanations of university biology students for natural selection problems. In: Novak, JD. Proceedings of the Second International Seminar on Misconceptions and Educational Strategies in Science and Mathematics, vol II. Ithaca: Department of Education, Cornell University; 1987;224–32.

Jørgensen C, Enberg K, Dunlop ES, Arlinghaus R, Boukal DS, Brander K, et al. Managing evolving fish stocks. Science. 2007;318:1247–8. doi: 10.1126/science.1148089 .

Jungwirth E. The problem of teleology in biology as a problem of biology-teacher education. J Biol Educ. 1975a;9:243–6.

Jungwirth E. Preconceived adaptation and inverted evolution. Aust Sci Teachers J. 1975b;21:95–100.

Jungwirth E. Should natural phenomena be described teleologically or anthropomorphically?—a science educator’s view. J Biol Educ. 1977;11:191–6.

Kampourakis K, Zogza V. Students’ preconceptions about evolution: how accurate is the characterization as “Lamarckian” when considering the history of evolutionary thought? Sci Edu 2007;16:393–422.

Kampourakis K, Zogza V. Students’ intuitive explanations of the causes of homologies and adaptations. Sci Educ. 2008;17:27–47. doi: 10.1007/s11191-007-9075-9 .

Kampourakis K, Zogza V. Preliminary evolutionary explanations: a basic framework for conceptual change and explanatory coherence in evolution. Sci Educ. 2009; in press.

Kardong KV. An introduction to biological evolution. 2nd ed. Boston: McGraw Hill; 2008.

Kargbo DB, Hobbs ED, Erickson GL. Children's beliefs about inherited characteristics. J Biol Educ. 1980;14:137–46.

Kelemen D. Why are rocks pointy? Children's preference for teleological explanations of the natural world. Dev Psychol. 1999a;35:1440–52. doi: 10.1037/0012-1649.35.6.1440 .

Kelemen D. Function, goals and intention: children's teleological reasoning about objects. Trends Cogn Sci. 1999b;3:461–8. doi: 10.1016/S1364-6613(99)01402-3 .

Kelemen D, Rosset E. The human function compunction: teleological explanation in adults. Cognition. 2009;111:138–43. doi: 10.1016/j.cognition.2009.01.001 .

Keown D. Teaching evolution: improved approaches for unprepared students. Am Biol Teach. 1988;50:407–10.

Lawson AE, Thompson LD. Formal reasoning ability and misconceptions concerning genetics and natural selection. J Res Sci Teach. 1988;25:733–46. doi: 10.1002/tea.3660250904 .

MacFadden BJ, Dunckel BA, Ellis S, Dierking LD, Abraham-Silver L, Kisiel J, et al. Natural history museum visitors' understanding of evolution. BioScience. 2007;57:875–82.

Mayr E. The growth of biological thought. Cambridge: Harvard University Press; 1982.

Mayr E. What evolution Is. New York: Basic Books; 2001.

McCloskey M, Caramazza A, Green B. Curvilinear motion in the absence of external forces: naïve beliefs about the motion of objects. Science. 1980;210:1139–41. doi: 10.1126/science.210.4474.1139 .

Moore R, Mitchell G, Bally R, Inglis M, Day J, Jacobs D. Undergraduates' understanding of evolution: ascriptions of agency as a problem for student learning. J Biol Educ. 2002;36:65–71.

Nehm RH, Reilly L. Biology majors' knowledge and misconceptions of natural selection. BioScience. 2007;57:263–72. doi: 10.1641/B570311 .

Nehm RH, Schonfeld IS. Does increasing biology teacher knowledge of evolution and the nature of science lead to greater preference for the teaching of evolution in schools? J Sci Teach Educ. 2007;18:699–723. doi: 10.1007/s10972-007-9062-7 .

Nehm RH, Poole TM, Lyford ME, Hoskins SG, Carruth L, Ewers BE, et al. Does the segregation of evolution in biology textbooks and introductory courses reinforce students' faulty mental models of biology and evolution? Evo Edu Outreach. 2009;2: In press.

Nelson CE. Teaching evolution effectively: a central dilemma and alternative strategies. McGill J Educ. 2007;42:265–83.

Nelson CE. Teaching evolution (and all of biology) more effectively: strategies for engagement, critical reasoning, and confronting misconceptions. Integr Comp Biol. 2008;48:213–25. doi: 10.1093/icb/icn027 .

Packard AS. Lamarck, the founder of evolution: his life and work with translations of his writings on organic evolution. New York: Longmans, Green, and Co; 1901.

Palumbi SR. Humans as the world's greatest evolutionary force. Science. 2001;293:1786–90. doi: 10.1126/science.293.5536.1786 .

Passmore C, Stewart J. A modeling approach to teaching evolutionary biology in high schools. J Res Sci Teach. 2002;39:185–204. doi: 10.1002/tea.10020 .

Pedersen S, Halldén O. Intuitive ideas and scientific explanations as parts of students' developing understanding of biology: the case of evolution. Eur J Psychol Educ. 1992;9:127–37.

Pennock RT. Learning evolution and the nature of science using evolutionary computing and artificial life. McGill J Educ. 2007;42:211–24.

Prinou L, Halkia L, Skordoulis C. What conceptions do Greek school students form about biological evolution. Evo Edu Outreach. 2008;1:312–7. doi: 10.1007/s12052-008-0051-x .

Ridley M. Evolution. 3rd ed. Malden: Blackwell; 2004.

Robbins JR, Roy P. The natural selection: identifying & correcting non-science student preconceptions through an inquiry-based, critical approach to evolution. Am Biol Teach. 2007;69:460–6. doi: 10.1662/0002-7685(2007)69[460:TNSICN]2.0.CO;2 .

Rose MR, Mueller LD. Evolution and ecology of the organism. Upper Saddle River: Prentice Hall; 2006.

Rutledge ML, Mitchell MA. High school biology teachers' knowledge structure, acceptance & teaching of evolution. Am Biol Teach. 2002;64:21–7. doi: 10.1662/0002-7685(2002)064[0021:HSBTKS]2.0.CO;2 .

Scharmann LC. Enhancing an understanding of the premises of evolutionary theory: the influence of a diversified instructional strategy. Sch Sci Math. 1990;90:91–100.

Settlage J. Conceptions of natural selection: a snapshot of the sense-making process. J Res Sci Teach. 1994;31:449–57.

Shtulman A. Qualitative differences between naïve and scientific theories of evolution. Cognit Psychol. 2006;52:170–94. doi: 10.1016/j.cogpsych.2005.10.001 .

Sinatra GM, Southerland SA, McConaughy F, Demastes JW. Intentions and beliefs in students' understanding and acceptance of biological evolution. J Res Sci Teach. 2003;40:510–28. doi: 10.1002/tea.10087 .

Sinatra GM, Brem SK, Evans EM. Changing minds? Implications of conceptual change for teaching and learning about biological evolution. Evo Edu Outreach. 2008;1:189–95. doi: 10.1007/s12052-008-0037-8 .

Southerland SA, Abrams E, Cummins CL, Anzelmo J. Understanding students' explanations of biological phenomena: conceptual frameworks or p-prims? Sci Educ. 2001;85:328–48. doi: 10.1002/sce.1013 .

Spiegel AN, Evans EM, Gram W, Diamond J. Museum visitors' understanding of evolution. Museums Soc Issues. 2006;1:69–86.

Spindler LH, Doherty JH. Assessment of the teaching of evolution by natural selection through a hands-on simulation. Teach Issues Experiments Ecol. 2009;6:1–20.

Stauffer RC (editor). Charles Darwin's natural selection: being the second part of his big species book written from 1856 to 1858. Cambridge, UK: Cambridge University Press; 1975.

Stearns SC, Hoekstra RF. Evolution: an introduction. 2nd ed. Oxford, UK: Oxford University Press; 2005.

Strevens M. The essentialist aspect of naive theories. Cognition. 2000;74:149–75. doi: 10.1016/S0010-0277(99)00071-2 .

Sundberg MD. Strategies to help students change naive alternative conceptions about evolution and natural selection. Rep Natl Cent Sci Educ. 2003;23:1–8.

Sundberg MD, Dini ML. Science majors vs nonmajors: is there a difference? J Coll Sci Teach. 1993;22:299–304.

Tamir P, Zohar A. Anthropomorphism and teleology in reasoning about biological phenomena. Sci Educ. 1991;75:57–67. doi: 10.1002/sce.3730750106 .

Tidon R, Lewontin RC. Teaching evolutionary biology. Genet Mol Biol. 2004;27:124–31. doi: 10.1590/S1415-475720054000100021 .

Vlaardingerbroek B, Roederer CJ. Evolution education in Papua New Guinea: trainee teachers' views. Educ Stud. 1997;23:363–75. doi: 10.1080/0305569970230303 .

Wilson DS. Evolution for everyone: how to increase acceptance of, interest in, and knowledge about evolution. PLoS Biol. 2005;3:e364. doi: 10.1371/journal.pbio.0030364 .

Wood-Robinson C. Young people's ideas about inheritance and evolution. Stud Sci Educ. 1994;24:29–47. doi: 10.1080/03057269408560038 .

Zirkle C. The early history of the idea of the inheritance of acquired characters and of pangenesis. Trans Am Philos Soc. 1946;35:91–151. doi: 10.2307/1005592 .

Zohar A, Ginossar S. Lifting the taboo regarding teleology and anthropomorphism in biology education—heretical suggestions. Sci Educ. 1998;82:679–97. doi: 10.1002/(SICI)1098-237X(199811)82:6<679::AID-SCE3>3.0.CO;2-E .

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Natural Selection

Natural selection is one of the basic mechanisms of evolution, along with mutation, migration, and genetic drift.

Darwin’s grand idea of evolution by natural selection is relatively simple but often misunderstood. To see how it works, imagine a population of beetles:

If you have variation, differential reproduction, and heredity, you will have evolution by natural selection as an outcome. It is as simple as that.

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See how the simple mechanisms of natural selection can  produce complex structures , learn about  misconceptions regarding natural selection , or review the history of the idea of natural selection .

Learn more about natural selection in context:

• Angling for evolutionary answers: The work of David O. Conover , a research profile.
• Battling bacterial evolution: The work of Carl Bergstrom , a research profile.
• Natural slection from the gene up: The work of Elizabeth Dahlhoff and Nathan Rank , a research profile.

Teach your students about natural selection:

• Clipbirds , a classroom activity for grades 6-12.
• Breeding bunnies , a classroom activity for grades 9-12.

Find  additional lessons, activities, videos, and articles  that focus on natural selection.

Reviewed and updated June, 2020.

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Module 13: Evolution and Natural Selection

Evolution and natural selection.

The process of biological evolution can be accurately defined as “descent with modification.” This definition includes microevolution (changes in allele frequency of a population over time) and macroevolution (the descent of different species from a shared common ancestor over many generations). Evolution relies on four processes that function as the basic mechanisms of evolutionary change:

• Mutation.  Mutations are the ultimate source of variation in a population, resulting in changes in the genetic makeup of an individual.
• Migration.  The allele frequency of a population can change if members of an existing population leave, or new members join.
• Genetic Drift.  Genetic drift happens when allele frequencies change due to purely random factors. For example, if a person accidentally stepped on a population of beetles and randomly killed all the brown beetles in the population, the allele frequency of the population would certainly change, but the cause of the change is completely random. This is an example of genetic drift. It is most significant in small populations.
• Reproduction.  Species reproduce in excess of the numbers that can survive.
• Variation.  All sexually reproducing species vary in characteristics.
• Heredity.  Traits can be passed from one generation to the next.
• Fitness.  Those individuals with hereditary characteristics that have survival value, i.e., improved fitness, are more likely to survive and reproduce compared with less fit individuals. Be careful here, because the word “fitness” does not refer to physical fitness or healthiness! This word is being used in a very specific way to mean “successful reproduction.” Fit individuals make more babies. This is not necessarily true of our common use of the word!

If these four processes are coupled with reproductive isolation, then speciation (the formation of a new species) can occur. Reproductive isolation occurs by some mechanism that can isolate diverging populations so as to prevent interbreeding. Given sufficient time, a population that is isolated from the original population can diverge physically and/or behaviorally to the point where it is a distinct species. There is a variety of isolating mechanisms that can prevent gene flow from occurring. One example is the presence of geographical barriers such as mountain ranges or islands that prevent gene flow between separated populations.

Part 1: Natural Selection Exercise—Generation 1

This exercise illustrates the effect of natural selection on populations of predators and prey. Students, in groups of four, will represent predators, each with a different adaptation for capturing their prey. The prey will consist of different species represented by different colored beans.

• Each team of 4 students will count out exactly 100 dried beans of each color.
• If the weather is poor, it is dark outside, or your instructor would rather, your habitat will be a tray of sediment in the classroom.
• If the weather is lovely, or your instructor is adventurous, you will do this lab outside. Each team will mark off a 1m × 1m “habitat” in the grass using yarn, a meter stick, and wood stakes.
• All “prey” are confined to the habitat, wherever it is!
• Each student (predator) will have a different feeding apparatus: A fork, spoon, knife or forceps.
• Predators must only use their capture device to capture prey.
• Predators may not scoop prey up with their cup.
• If predators “eat” too much of the environment, they will become constipated and DIE.
• Each predator determines the number of prey captured and records results in Data Sheet: Generation 1.
• Calculate and fill in the remaining statistics on the data sheet (see example below).

Data Sheet: Generation 1

Example of Data Collection and Analysis for Generation 1

# of This Bean That Survived = population size – total kills

% of This Bean That Survived = (# survived/population size) x 100

% Total Population = (# survived/total survived) x 100

Part 2: Natural Selection Exercise—Generation 2

The predator with the lowest capture percentage will go “extinct” and will not participate in the next exercise. The predator with the highest capture percentage will reproduce itself and the “offspring” will participate in the next exercise. The surviving prey will also survive and reproduce.

• The person with the lowest capture percentage (as calculated in the previous exercise) will “die” and turn in their feeding device.
• If the Fork won the first round and the Spoon lost, then in the second round, there will be two  Forks and zero  Spoons. There will also be one Knife and one pair of Forceps.
• If there are 40 surviving black beans, you will add another 40 black beans to the habitat, so there are a total of 80 black beans in the habitat for round 2.
• Repeat the procedure you carried out in Part 1. Collect data for Generation 2.

Data Sheet: Generation 2

Note: For population size in generation 2, multiply the number that survived in generation 1 by two.

Part 3: Natural Selection Exercise—Generation 3

The winning predator will reproduce again and the surviving prey will also reproduce (just like they did in the previous exercise). Collect and record new data.

Data Sheet: Generation 3

Note: For population size in generation 3, multiply the number that survived in generation 2 by two.

Part 4: Pie Chart Analysis of Predator and Prey Populations

Now that you have collected data from three generations of predator and prey populations, you will use the data to create a set of pie charts to help you interpret your results. The first pair of pie charts represent the data from the original predator and prey populations. Use these examples to create your own charts using your group’s data.

End of First Generation

End of Second Generation

End of Third Generation

Lab Questions

• Explain in your own words the process of natural selection.
• What conclusions can you draw regarding the effect of natural selection on the predator populations in this exercise?
• What conclusions can you draw regarding the effect of natural selection on the prey populations in this exercise?
• What do you predict would happen to both predator and prey populations if the habitat for this exercise was changed? Give an example.
• Relate the concept of natural selection  to the process of evolution .
• Is natural selection the only way evolution occurs? Explain.
• 8 + 14 + 10 +15 ↵
• 100 – 47 ↵
• 53 + 6 + 23 + 41 ↵
• (53/100) × 100 (6/100) × 100 ↵
• (53/123) × 100 ↵
• Biology Labs . Authored by : Wendy Riggs . Provided by : College of the Redwoods . Located at : http://www.redwoods.edu . License : CC BY: Attribution

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Natural Selection: Uncovering Mechanisms of Evolutionary Adaptation to Infectious Disease

In the 1940s, J. B. S. Haldane observed that many red blood cell disorders, such as sickle-cell anemia and various thalassemias, were prominent in tropical regions where malaria was endemic (Haldane, 1949; Figure 1). Haldane hypothesized that these disorders had become common in these regions because natural selection had acted to increase the prevalence of traits that protect individuals from malaria. Just a few years later, Haldane's so-called "malaria hypothesis" was confirmed by researcher A. C. Allison, who demonstrated that the geographical distribution of the sickle-cell mutation in the beta hemoglobin gene ( HBB ) was limited to Africa and correlated with malaria endemicity. Allison further noted that individuals who carried the sickle-cell trait were resistant to malaria (Allison, 1954).

Allison's confirmation of Haldane's hypothesis provided the first elucidated example of human adaptation since natural selection had been proposed a century earlier. Today, this and other demonstrations of natural selection help point researchers toward biological mechanisms of resistance to infectious disease . Moreover, such examples also shed light on the ways in which pathogens rapidly evolve to remain agents of human morbidity and mortality.

Selection for Malaria Resistance: A Closer Look

Since Allison and Haldane's work, the action of natural selection on genetic resistance to malaria has been shown in a multitude of contexts (Kwiatkowski, 2005). Indeed, the sickle-cell variant (i.e., the HbS allele ) has been identified in four distinct genetic backgrounds in different African populations, suggesting that the same mutation arose independently several times through convergent evolution . Beyond HbS, other distinct mutations in the HBB gene have generated the HbC and HbE alleles , which arose and spread in Africa and in Southeast Asia, respectively.

The various HBB alleles aren't alone in offering protection against malaria, however. The geographic distributions of several other red blood cell disorders, including a-thalassemia, G6PD deficiency, and ovalocytosis, correlate to malaria endemicity, and the diseases also are linked to malaria resistance. An even more striking worldwide geographical difference exists for a mutation in the Duffy antigen gene ( FY ), which encodes a membrane protein used by the Plasmodium vivax malaria parasite to enter red blood cells. This mutation disrupts the protein, thus conferring protection against P. vivax malaria, and it occurs at a prevalence of 100% throughout most of sub-Saharan Africa yet is virtually absent outside of Africa. Moreover, through convergent evolution , an independent mutation in FY that decreases this gene's expression has also become prevalent in Southeast Asia.

So, why has malaria exerted such strong selective pressure? Scientists now know the answer. Malaria is arguably one of the human population 's oldest diseases and greatest causes of morbidity and mortality. Research indicates that the malaria-causing parasite Plasmodium falciparum has occurred in human populations for approximately 100,000 years, with a large population expansion in the last 10,000 years as human populations began to move into settlements (Hartl, 2004). P. falciparum , together with the other malaria species , P. vivax , P. malariae, and P. ovale , infects hundreds of millions of people worldwide each year, and kills more than 1 million children annually (World Health Organization, 2000). Because this disease is so devastating, humans have had to evolve adaptive traits to survive in the face of this infectious condition over the past few millennia (Kwiatkowski, 2005).

Broader Implications of Natural Selection for Investigating Infectious Disease

While malaria is the best-understood example of an infectious disease that has driven human evolution, numerous other infectious diseases have also acted in human populations over generations, thus allowing resistance alleles to emerge and spread over time (Diamond, 2005). Based on historical records from the last millennium, these diseases might include smallpox in ancient Europe and in Native American populations, as well as cholera, tuberculosis, and bubonic plague in Europe. Many diseases in Africa have likely been endemic for even longer, such as numerous diarrheal diseases, yellow fever, and Lassa hemorrhagic fever.

Today, with access to heretofore unprecedented data sets for the study of human genetic variation , researchers can exploit the genetic signatures of natural selection using novel analytical methods. In this way, they can identify genetic variants conferring resistance to infectious diseases that have spread through human populations over time. These studies will help elucidate natural mechanisms of defense and perhaps uncover novel evolutionary pressures. Moreover, the same tools that have revolutionized the study of natural selection in humans will also make unprecedented studies of pathogens possible.

Investigating the signatures of natural selection can help elucidate the evolutionary adaptations that have allowed humans to withstand some of our most complex and challenging selective agents. In particular, researchers can look for variants that might be readily detected in genetic association studies; for distinctive, detectable patterns of genetic variation in the human genome ; and for clues as to how pathogens themselves evolve so rapidly.

Searching for Variants via Association Studies

By driving highly protective variants to high prevalence, natural selection produces variants that might be readily detected in genetic association studies to help elucidate the biological basis of disease resistance. The classic examples of host genetic factors that play a role in resistance to malaria, such as HbS, are some of the strongest and most robust signals of genetic susceptibility to infectious disease (Hill, 2006). This is because natural selection acts to increase the prevalence of highly advantageous alleles, over time generating common resistance alleles of especially strong effect. For example, a study of genetic susceptibility of HbS in the Gambia detected a significant level of protection using just 315 cases and 583 controls (Ackerman et al. , 2005). By studying other ancient selective pressures in which common resistance alleles of strong effect are acting, scientists may have the power to detect a genetic association even with small sample sizes.

In contrast, no single highly protective variant for emergent diseases like HIV and tuberculosis (in Africa) would have had time to spread. For these diseases, resistance appears to be modulated by many rare genetic variants, most with modest protective effect, and genetic studies require extremely large sample sizes (Hill, 2006). This is likely not a biological but, rather, a historical difference. Indeed, hundreds of structural and regulatory mutations exist in HBB , such as HbS, HbE, or HbC, but in populations under malaria selective pressure , a single highly protective variant will often dominate (Kwiatkowski, 2005). Moreover, many variants nearby on the chromosome will rise in prevalence in the population through genetic hitchhiking , such that other nearby linked alleles can serve as proxies for the underlying causal allele in genetic association studies, further enhancing researchers' ability to detect an association. Thus, natural selection may produce important genetic resistance loci that can more easily be detected in association studies.

Searching for Patterns of Variation

As genetic variants conferring resistance to infectious diseases spread through human populations over time through natural selection, they leave distinctive, detectable patterns of genetic variation in the human genome. These signals of selection can uncover novel resistance alleles or even novel evolutionary pressures. Also, as previously mentioned, as advantageous alleles under positive selection rise in prevalence, variants at nearby locations on the same chromosome (linked alleles) also rise in prevalence. Such genetic hitchhiking leads to a " selective sweep " that alters the typical pattern of genetic variation in the region. Selective sweeps produce numerous detectable signals of selection (Nielsen, 2005; Sabeti et al., 2006). As tests for selection have been applied to newly available genetic variation data across the human genome, many of the top signals of selection that have been identified have been at genes and alleles known to be involved with malaria susceptibility, including HBB , FY , CD36 , and HLA . These signals were identified in just 90 individuals randomly chosen from the population, and they could have been identified without prior knowledge of a specific variant or selective advantage .

Surveys of natural selection can not only identify new resistance variants for known selective pressures, but they can also potentially uncover previously unrecognized selective pressures. For example, in a genome survey of the Yoruba people of Nigeria, two of the top signals of selection were at genes ( LARGE and DMD ) biologically linked to the Lassa hemorrhagic fever virus (Sabeti et al ., 2007). While little studied, Lassa virus in fact infects many millions of West Africans, and based on oral records and epidemiology , it is likely to be an ancient disease (Richmond & Baglole, 2003). Researchers have documented that in several affected West African populations, between 50% and 90% of individuals are resistant to the virus, suggesting that protective alleles emerged at some point (McCormick & Fisher-Hoch, 2002). This finding could open new avenues for research and shine light on other important pathogens in human history.

Searching for Clues about Pathogen Evolution

The same tools that revolutionized the study of natural selection in humans are now making unprecedented studies of pathogens possible, allowing scientists to better understand how these organisms rapidly evolve to remain agents of human morbidity and mortality. Pathogens are perhaps the most intriguing of all the forces shaping humans. They have had a tremendous impact on our evolution, and they, themselves, evolve over time. The great effect that pathogens have exerted on the human genome is demonstrated by positive selection for traits such as sickle-cell hemoglobin (Sabeti et al ., 2006). Natural human defenses have similarly exerted strong pressures on the genomes of pathogens, as has the use of drugs and vaccines (Volkman et al. , 2007). By studying genetic diversity in pathogens, researchers can examine how they have evolved to avoid human immune defenses and therapeutics. Furthermore, scientists can investigate in real time the evolutionary consequences of new vaccines and drugs, with the goal of developing better intervention strategies.

Future Endeavors

Investigation of the links between natural selection and disease resistance has revealed some of the forces that have shaped our species, and the findings of these studies have direct implications for human health. However, research thus far represents just a first glimpse of a vast new landscape. In the years to come, new technologies and analytic methods will enable researchers to learn even more about the genetic basis of evolutionary adaptations that have allowed humans to withstand a wide variety of complex and challenging selective agents.

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David N. Reznick, Cameron K. Ghalambor, Selection in Nature: Experimental Manipulations of Natural Populations, Integrative and Comparative Biology , Volume 45, Issue 3, June 2005, Pages 456–462, https://doi.org/10.1093/icb/45.3.456

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Numerous studies have documented evolution by natural selection in natural populations, but few are genuine selection experiments that are designed and then executed in nature. We will focus on these few cases to illustrate what can be learned from field selection experiments alone or field and laboratory selection experiments together that cannot be learned from laboratory experiments alone. Both types of study allow us to evaluate cause and effect relationships because a planned experiment can be accompanied by a more direct evaluation of the factors that cause evolution. A unique benefit of field experiments is that they give us the opportunity to measure the rate and magnitude of selection in nature. We have found that this rate is far greater than one might imagine based on observations of the fossil record. A combination of field and laboratory selection experiments has revealed the importance of population size and structure in shaping the genetics of adaptation. For example, laboratory selection experiments on insecticide resistance tend to attain resistance though polygenic inheritance. The evolution of insecticide resistance in nature often eventually yields to single genes of large effect that are rare but, once they arise, represent a higher fitness solution to resistance and spread among populations. Finally, field studies enable us to test evolutionary theory in a context in which all of the tradeoffs associated with a trait are realized; in the laboratory, organisms may be shielded from the fitness tradeoffs associated with the evolution of a trait. For example, we have compared the patterns of senescence in guppies from high and low mortality rate environments in the laboratory and in the field. In the laboratory, guppies from high predation environments had delayed senescence relative to those from low predation environments. In the field the apparent relationship is the opposite. One hypothesis for this difference is that a tradeoff associated with the evolution of the high predation life history is a decrease in the investment in the immune system. Such a sacrifice would be evident in nature where there is exposure to disease and parasites but less so in the laboratory, which is relatively disease and parasite free.

This symposium is dominated by laboratory selection experiments. The natural reason for this pattern of representation is that virtually all selection experiments have been done in a laboratory setting. Our goal is to summarize the small number of selection experiments that have been done in nature, then to highlight what such studies can contribute to our understanding of evolution that cannot be learned from laboratory studies alone. We will argue that there is one important message derived from field experiments that can only be learned from such experiments and two messages that require a combination of field and laboratory work.

The goals of selection experiments done in a natural population are to characterize the process of evolution by natural selection and to test aspects of evolutionary theory in nature. The few such experiments that have been done share some important qualities. First, they are preceded by extensive, comparative field studies that characterize variation in the study organisms and their environments. Second, they are designed to test hypotheses that were suggested by the prior field studies and by associated evolutionary theory. Third, they remain part of a continued interplay between experiments and field studies. Field experiments are thus embedded in larger programs of study and have designs that are inspired by these programs, rather than being stand-alone experiments.

There are only two experiments thus far that fully qualify as formal selection experiments done in nature. One was performed on guppies found in streams that drain the Northern Range Mountains of Trinidad ( e.g., Endler, 1980 ; Reznick et al. , 1990 ) and the other on Anolis lizards introduced to lizard-free islands in the Caribbean ( e.g., Schoener and Schoener, 1983 ; Losos et al. , 1997 , 2001 ). However, there are many other studies that, while not formal field selection experiments, have also been done in a context that allow us to associate the process of adaptation with a dated event and appropriate controls and hence to make direct inferences about the process of evolution ( e.g., Carroll and Boyd, 1992 ; Grant and Grant, 2002 ; Hendry et al. , 2000 ; Lee, 1999 ). We will make use of these additional studies in our review since the information that they yield is comparable to what we have learned from formal experiments. We will first briefly review the two formal selection experiments.

The evolution of color patterns and life histories in guppies

The Northern Range Mountains of Trinidad contain a seasonal tropical rainforest that receives up to four meters of rain per year. They are well supplied with streams that flow throughout the year. These streams are occupied on the south slope by a subset of the fish that characterize freshwater rivers in the Orinoco Basin in Venezuela, including cichlids and characins. The streams on the north slope contain fish that are derived from more typically marine species, including gobies and mullets. Both sets of streams have drainages that are broken up by steep, karst topography. The waterfalls that are typical of such topography often serve as upstream barriers to the dispersal of some of the larger, predatory species of fish. Guppies are distributed more widely than most other fish species, so they are frequently found co-occurring with predatory fish below barrier waterfalls and are free of such predation above such barriers. Guppies have a dramatic sexual dimorphism. Males have determinate growth, are brightly colored and their color patterns are highly polymorphic. Females have indeterminate growth, so they are generally larger than males and lack the bright pigmentation of males.

Endler (1978) found that male guppies from high predation environments have fewer, smaller color spots than their counterparts from low predation environments. He hypothesized that this pattern was caused by a balance between females preferring to mate with brightly colored males and brightly colored males being more susceptible to predation. When predators are absent, female preference results in the evolution of brighter coloration. When predators are present, they limit the effects of female preference by preying preferentially on more brightly colored males because they are also more conspicuous.

Reznick (1982) and Reznick and Endler (1982) found that the presence of predators was also associated with guppies that attained maturity at an earlier age and reproduced more frequently. They had more offspring in each litter, the size of individual offspring was smaller, and the quantity of consumed resources that was devoted to reproduction was larger than in guppies from low predation localities. These patterns were shown to have a genetic basis because they persisted in the second generation of lab-born guppies that were reared on controlled levels of food availability. We hypothesized that these patterns were caused by the differences in mortality rate between high and low predation localities. Specifically, we hypothesized that guppies from high predation environments sustain higher adult mortality rates because many of the predators were known to prey preferentially on the larger size classes. In contrast, guppies from low predation localities should experience selective predation on immature size classes because the one fish predator found there, Rivulus hartii , is gape limited and preys primarily on the smaller size classes. The hypothesized association between mortality and life histories was based on predictions from life history theory ( e.g., Charlesworth, 1980 ; Gadgil and Bossert, 1970 ; Law, 1979 ; Michod, 1979 ). We later directly estimated mortality rates with mark-recapture studies ( Reznick et al. , 1996 ) and showed that these general patterns were obtained.

Both of these studies demonstrate that the patterns in male coloration and life histories are found across a diversity of streams from throughout the Northern Range Mountains (see also Reznick et al. , 1996 a ; Reznick and Bryga, 1996 ). There are thus many replicate streams which show the same patterns and provide the raw material for subsequent experiments. Both studies also reveal that differences between high and low predation environments can be seen over very small distances, such as in samples collected only tens of meters apart from above and below barrier waterfalls that serve to prevent upstream dispersal of predators ( Endler, 1978 ; Reznick and Endler, 1982 ). Since such sites are identical in all regards, except for the presence or absence of predators, it seems likely that predators are responsible for the observed differences.

The actual experiments exploited the discontinuities in the distribution of guppies and guppy predators caused by barrier waterfalls and treated streams as if they were giant test tubes. In two cases, we found streams that had a waterfall that served as a barrier to all species of fish except R. hartii . This fish has superior dispersal capabilities, because it is able to leave streams on rainy nights, hop across the forest floor, and disperse to ephemeral pools and portions of streams above barrier waterfalls. We thus often find streams above dramatic waterfalls that only contain R. hartii . In both cases, we collected guppies from the high predation site below the barrier waterfall and introduced them into the previously guppy-free low predation site above the barrier waterfall. We consider the descendants of the introduced guppies to be our experimental treatment and use those from the high predation site below the barrier waterfall as a control. Inferences about the evolution of male coloration or life history traits are based on a comparison of experimental and control guppies.

A second type of experiment involved a barrier waterfall on the Aripo River. This barrier represented the upstream limit for a suite of larger predators, but not for guppies, R. hartii , and a few other species of fish. Here we collected predators from below the barrier and introduced them over the barrier. Their subsequent upstream dispersal was limited by the presence of another barrier waterfall shortly upstream. This experimental treatment increased the mortality rate of the affected guppies. Their evolution was evaluated with respect to control guppies collected from the high predation site below the barrier waterfall and others collected from the low predation site upstream of the secondary barrier waterfall.

Together we have two experiments in which guppy mortality rates were either reduced or increased in the field. With regard to male coloration, Endler predicted that the release from predation would result in the predominance of female preferences for brightly colored males and hence the evolution of males with larger spots in the introduction site in comparison to the high predation control. This prediction has only been evaluated in one of the two experiments in which guppies were moved from a high to a low predation locality. Males from the introduction site had significantly larger spots than those from the control site, only two years after the introduction ( Endler, 1980 ). In the case of life history traits, the goal was to test a particular facet of life history theory in nature. Transplanting guppies from a high to a low predation environment was predicted to select for individuals that attain maturity at a later age and have a lower rate of investment in reproduction. We also expected them to produce fewer, larger offspring than their counterparts from the high predation control. Transplanting predators to a low predation site was predicted to select for individuals that have an earlier age at maturity relative to controls found above the secondary barrier waterfall. All of these predictions were upheld. In one of the replicate introductions of guppies from a high to low predation site, male age and size at maturity had evolved in the predicted direction within four years ( Reznick and Bryga, 1987 ), and female age and size at maturity changed as predicted within seven years ( Reznick et al. , 1990 ). In the second introduction of guppies from a high to low predation site, male age and size at maturity, female age and size at maturity, reproductive effort, offspring size, and offspring number had all changed as predicted within 11 years ( Reznick et al. , 1990 ). When mortality rate was increased by adding predators, the age at maturity of males and females both decreased relative to the low predation control after five years ( Reznick, 1997 ).

In all of these studies the genetic basis of differences between high and low predation sites has been evaluated by rearing guppies in a common laboratory environment for at least two generations. Such “common garden” experiments remove or greatly reduce variation due to environmental or maternal effects and provide evidence on whether genetic change has occurred between populations.

The evolution of limb morphology in Anolis lizards

The second example of selection experiments done in nature was executed by Tom Schoener, Jonathan Losos and colleagues on Anolis lizards. This research was preceded by extensive studies of the distribution and adaptive radiation of Anolis lizards in the Caribbean ( e.g., Williams, 1972 , 1983 ; Schoener and Schoener, 1983 ; Losos, 1994 ; Losos et al. , 1994 , 1997 , 1998 , 2001 ). Earlier studies had found that each of the islands making up the Greater Antilles has a similar assemblage of Anolis lizards that are specialized for particular habitats and lifestyles, termed “ecomorphs” ( Williams, 1972 , 1983 ). For example, a number of islands have ecomorphs referred to as crown giants, which are large species that live in tree canopies. Other ecomorphs include twig specialists that are small, short-legged species that tend to be found on branches of small diameter, and trunk-crown specialists, which have well-developed toe pads and elongated bodies that tend to be found on tree trunks and branches from eye level to high in the tree ( e.g., Losos, 1994 ; Losos et al. , 1994 ). Laboratory and field studies confirmed that these relationships between morphology and habitat have an adaptive basis with respect to locomotor performance ( Irschick and Losos, 1998 , 1999 ). DNA-based phylogenies demonstrated that similar adaptive radiations have occurred independently and repeatedly on different islands. For example, trunk-crown anoles tend to be more closely related to Anolis species on the same island with different body shapes and ecological specializations than they are to trunk-crown anoles on other islands ( Losos et al. , 1998 ). These associations between habitat preference, morphology, and performance suggest that these differences in morphology evolved independently and repeatedly as adaptations to specific environmental conditions rather than evolving once and spreading through dispersal. If the interspecific and interpopulation differences in limb morphology represent locomotor adaptations to specific types of vegetation and habitats, then populations that have adapted to islands with different structured communities should evolve similar differences in limb morphology as seen in natural populations.

In 1977 and 1981, Anolis sagrei from a common source population was introduced to 14 previously lizard-free islands in the Bahamas. These islands varied in the type of vegetation that they had, yielding predictions for how limb morphology should evolve as each new population adapted to its island. Losos et al. (1997) found a significant association between morphology and vegetation structure after a time interval of 10–14 years. It remains to be seen whether or not these differences are a function of phenotypic plasticity or changes in the genetic composition of the population ( Losos et al. , 2001 ). However, based on these results it is clear that the potential for relatively rapid adaptive differentiation in nature is possible. This rapid adaptive differentiation is also seen in the most recent set of experiments. Previous work has shown that on islands where the predatory and ground-dwelling curly-tailed lizard ( Leiocephalus carinatus ) is present, populations of A. sagrei shift habitat use by moving higher up in the vegetation ( Losos, 1994 ). In 2003, L. carinatus was introduced to six small islands in the Bahamas resulting in a rapid adaptive behavioral shift in habitat use in response to the new predator-induced selection pressures ( Losos et al. , 2004 ). Such experiments represent some of the first attempts to test the role of behavior and other phenotypically plastic traits driving adaptive evolution in nature and may provide considerable insight into mechanisms responsible for rapid evolutionary changes ( Losos et al. , 2004 ).

Field studies of guppies and Anolis lizards share key properties. Both use extensive prior field studies to evaluate patterns and develop hypotheses within a framework that allows for the formulation of a priori predictions. Both use manipulations that mimic events that frequently occur in nature. For example, the introduction of lizards mimics the continuous natural colonization (and often subsequent extinction) of these islands by lizards ( e.g., Losos et al. , 2001 ). Both test these hypotheses with manipulations of natural populations in a field setting. Both yield direct inferences about the process of evolution by natural selection. Finally, both studies are on-going and dynamic as results from previous observations and experiments inform future experiments.

While there are few formal experiments done in nature, there are a much larger number of studies that document evolution and adaptation in a context in which there is some history and hence information that is a close equivalent to a designed experiment, such as the accidental introduction of species into new environments (see Reznick and Ghalambor, 2001 ). We will use some examples of this sort of work to illustrate our points. Some important examples include: the characterization of how soapberry bugs ( Jadera haematoloma ) adapt to new, exotic plant hosts that were introduced into the bug's range at approximately known times ( Carroll and Boyd, 1992 ); the adaptation of marine rotifers that have recently invaded freshwater environments ( Lee, 1999 ; Lee and Bell, 1999 ); and the adaptation of yucca moths that exploit a new species of host ( Groman and Pellmyr, 2000 ). These and many more studies contain excellent analyses of adaptation to a new environment that can be associated with some historical change in the environment. All of them reveal information about responses to selection that is comparable to what has been learned from the two available field selection experiments.

Lesson 1: what unique knowledge can be derived from selection experiments in nature?

A key piece of information revealed by these contemporary studies of adaptation that cannot be obtained in laboratory selection experiments is that they yield estimates of the potential rate of evolution in nature. These studies consistently reveal that the rate of evolution seen in contemporary studies can be many orders of magnitude faster than rates that are inferred from the fossil record. Stearns (1992) , for example, updated Gingerich's (1983) comparisons of rates of evolution estimated from fossils, historical introductions, and artificial selection to include estimates of rates derived from the guppy introduction experiments. The seemingly small changes found in guppies were associated with rates of evolution that were of the same order of magnitude attained by artificial selection and four to seven orders of magnitude higher than seen in the fossil record. Virtually all of the other contemporary studies of evolution reveal similar results (see Hendry and Kinnison, 1999 ).

These results bear three important messages. The first message is that our perceptions of the rate of evolution that are based on the fossil record and that have played an important historical role in shaping our impressions of what evolution is like, are strongly biased and systematically underestimate the true potential rate of evolution. This bias occurs because inferences from the fossil record are based on long term averages that are likely to include long intervals of no change or reversals in the direction of change. The second message is that it might be more accurate to think of evolution as a series of relatively rapid, discrete events rather than prolonged, continuous change. Evolutionary trends, such as the fossil record, are an epiphenomenon of average long-term trends in these many discrete events. The third message is that the reason that evolution is not usually seen is not because it is too slow, as Darwin assumed, but because it is too fast. Evolution may well be concentrated in small, brief events and will only be seen if it is looked for, such as in the context of an experiment or as part of an individual mark-recapture study that is associated with the quantification of individual traits, as in work on Galapagos finches ( Grant and Grant, 1995 ) or side-blotched lizards ( Sinervo and Lively, 1996 ; Sinervo et al. , 2000 ), or in association with a cause that has a known time reference, as with the soapberry bugs.

There are two additional lessons that can be inferred from a combination of laboratory and field work.

Lesson 2: what is the importance of population structure?

Through the combination of the laboratory and field selection we also learn something about the importance of population structure and size. Lab selection imposes a specific population structure, meaning that investigators begin with a population of a given size and there is generally no continuing influx of new genes through migration. When selection occurs in nature, it will often play out in the context of a metapopulation, or many semi-isolated populations that are joined by gene flow. Thus, under natural conditions gene flow between populations can either oppose the fixation of beneficial alleles within a local population ( e.g., Slatkin, 1987 ) or facilitate the spread of alleles that confer a fitness advantage ( e.g., Lenormand et al. , 1998 ).

The evolution of insecticide resistance in insects has been evaluated multiple times in the lab and field and hence serves as a good example of the differences between the two selective environments. When selection was done on lab lines for insecticide resistance, the genetic basis for the evolution of resistance is caused by whatever polygenic variation was available in the founder population and resistance often involves many alleles of small effect ( e.g., McKenzie and Batterham, 1994 ). However, in nature resistance evolves through the substitution of single genes of large effect which can appear as rare mutations and spread through migration, in part because of the large number of semi-isolated populations exposed to selection and connected by long distance dispersal ( e.g., Lenormand et al. , 1998 ; Chevillon et al. , 1999 ). Assays of resistance in the field thus tend to reveal that it is caused by one or few genes of large effect ( McKenzie and Batterham, 1994 ). In this case, the discrepancy between laboratory and field assays may arise because laboratory lines are initiated from a small to moderate number of field collected individuals that may lack rare alleles that have large effects on resistance ( Roush and McKenzie, 1987 ). The bottom line is that lab selection can focus on a biased subset of the genetic mechanisms that cause a trait to evolve.

Lesson 3: how important are trade-offs among fitness traits in shaping the response to selection?

Our perception of the relative importance of trade-offs among fitness traits can often be a function of the environment in which these trade-offs are evaluated ( Reznick et al. , 2000 ). The differences among populations in the laboratory and field can be strongly affected by such a context-specific effect of trade-offs, often because organisms can be shielded from trade-offs in the lab that might have a large impact in nature. For example, the same alleles conferring resistance and a fitness benefit in the presence of insecticides impose a fitness cost in the absence of insecticides ( Chevillon et al. , 1999 ; Bourguet et al. , 2004 ). Such important pleiotropic effects are only revealed in the context of heterogenous environments and comparative studies of populations, or conditions more likely to be observed under field rather than laboratory conditions. Our studies of senescence in guppies from high and low predation environments in the lab versus the field illustrate another possible example of the context-specific nature of tradeoffs.

Evolutionary theory predicts that high predation environments, where we have seen the evolution of earlier maturity and increased reproductive investment, will also select for an earlier onset of senescence and shorter lifespan ( Medawar, 1952 ; Williams, 1957 ). Senescence in nature can be detected as an acceleration in mortality rate in older age groups. We tested this prediction in two contexts. First, we estimated the mortality rate of guppies in a natural low predation environment in comparison with an introduction experiment in which high predation guppies had been introduced into a low predation environment. Here we predicted that the introduced guppies, which now had the opportunity to live well beyond what their lifespan would be in the presence of predators, would have earlier senescence than the natural low predation population. Earlier senescence means that this acceleration in mortality rate should be detectable at an earlier age and may perhaps be more rapid in the introduced guppies relative to the natural low predation guppies.

As predicted, we found that high predation guppies had higher mortality rates overall and an earlier onset of an acceleration in mortality rate relative to low predation guppies ( Bryant and Reznick, 2004 ). This observation is unreplicated and is subject to alternative interpretations, but it is at least consistent with the prediction that higher extrinsic mortality rates, meaning mortality that is attributable to external causes such as predation, will also select for earlier senescence. We also tested this hypothesis in the laboratory, this time by comparing the grandchildren of wild-caught females from two high and two low predation localities. These localities represent two different drainages, each of which was represented by a high and low predation population. Prior genetic work argues that the differences in life history between high and low predation sites evolved independently in each drainage ( Carvalho et al. , 1991 ; Fajen and Breden, 1992 ), so the two drainages represent genuine duplicates of life history evolution. We found in both replicates, and in an earlier pilot study, that the guppies from high predation environments have deferred senescence relative to those from low mortality rate environments. The delayed senescence in high predation guppies is evident in their showing an acceleration of mortality rate at a later age, having longer average total lifespans, longer reproductive lifespans, and higher fecundity throughout their lives ( Reznick et al. , 2004 ). These laboratory results are thus the opposite of predictions derived from evolutionary theory.

Why would we find opposite results in the laboratory and the field? In the field mark-recapture assay, high predation guppies transplanted to a low predation environment had an earlier onset of senescence than the native low predation environment. In the laboratory, guppies derived from two high predation localities had delayed senescence in comparison to counterparts from low predation localities in the same drainage. One general explanation for the difference is that there is an important but unmeasured fitness trade-off associated with these life history traits that has a strong affect on natural populations but not on laboratory populations. One such trade-off could be the immune system. The immune system is costly to maintain and may be included in the complex of trade-offs associated with the evolution of life history traits ( e.g., Sheldon and Verhulst, 1996 ; Lochmiller and Deerenberg, 2000 ; Norris and Evans, 2000 ). For example, high predation guppies may be able to invest more in growth and reproduction early in life because they invest less in the immune system. In a natural high predation locality, they may well not live long enough to pay a price for this savings. In the laboratory, they are generally shielded from disease and parasites, so they will not pay this price, while in the field there will be a constant risk of exposure to disease. When high predation guppies are introduced into a low predation environment and have the opportunity to live longer, this trade-off may then become more apparent. It happens that the guppies in our introduction site did experience a high frequency of what appeared to be a bacterial infection. Such an infection is likely to have played a role in their higher mortality rate and earlier acceleration in mortality. It may also be the manifestation of such a trade-off between investment in growth and reproduction versus investment in the immune system. Whether or not this particular tradeoff accounts for the differences observed between our laboratory and field studies remains to be seen. It at least serves as a hypothesis for how such differences between the laboratory and field could arise and illustrates the added value of evaluating the consequences of selection in multiple environments. Similar conclusions have emerged from the comparisons of lifespans in laboratory strains versus wild strains of Caenorhabditis elegans ( Walker et al. , 2000 ), Mus musculus ( Miller et al. , 2002 ), or Drosophila melanogaster ( Linnen et al. , 2001 ).

Selection experiments can be done on natural populations. They reveal that adaptive evolution can be much more rapid than previously thought and open up the possibility of complimenting laboratory selection experiments with studies of natural populations. This conclusion is reinforced by a much larger number of non-experimental studies of adaptation that are linked to a time reference and hence allow us to make inferences about the rate of evolution and show that this inference of a high potential rate of evolution is obtainable in a diversity of organisms. A combination of evaluations of selection in the field and laboratory also reveals that population size and structure can affect the outcome and genetic basis of selection. Because the laboratory imposes a specific population size and structure that most often does not relate well to natural populations, the kind of response seen in the laboratory may also fail to represent how organisms are likely to evolve in the field. The repeatability of adaptive evolution at the phenotypic level in response to specific selection pressures has already been demonstrated under both field ( e.g., Reznick et al. 1996 a ; Losos et al. , 1997 ) and laboratory ( e.g., Rainey and Travisano, 1998 ; Travisano and Rainey, 2000 ) conditions. However, much remains to be learned about the repeatability of the underlying genetic architecture of these events. Future studies that specifically evaluate factors such as population size and structure under laboratory and field conditions could provide insight into this largely unexplored area of research. Finally, a combination of laboratory and field work reveals that studying organisms in the laboratory alone often means studying evolution in the absence of trade-offs that are normally present in nature. These trade-offs arise because organisms in nature typically occur within a mosaic of heterogeneous environments and under a diversity of selection pressures. Thus, pleiotropic effects and other fitness costs associated with alleles that would otherwise be favored in response to a given form of selection suggest that the absence of any fitness tradeoffs can yield a diversity of laboratory artifacts. In summary, we argue that our understanding of how phenotypes and genotypes respond to selection will be better informed by studies of adaptation in both laboratory and natural conditions.

From the Symposium Selection Experiments as a Tool in Evolutionary and Comparative Physiology: Insights into Complex Traits presented at the Annual Meeting of the Society for Integrative and Comparative Biology, 5–9 January 2004, at New Orleans, Louisiana.

E-mail: [email protected]

Bourguet , D. , T. Guillemaud, C. Chevillon, and M. Raymond. 2004 . Fitness costs of insecticide resistance in natural breeding sites of the mosquito Culex pipiens . Evolution , 58 128 -135.

Bryant , M. , and D. Reznick. 2004 . Comparative studies of senescence in natural populations of guppies. Am. Nat , 163 55 -68.

Carroll , S. B. , and C. Boyd. 1992 . Host race radiation in the soapberry bug: Natural history with the history. Evolution , 46 1052 -1069.

Carvalho , G. R. , P. W. Shaw, A. E. Magurran, and B. H. Seghers. 1991 . Marked genetic divergence revealed by allozymes among populations of the guppy Poecilia reticulata (Poeciliidae), in Trinidad. Biol. J. Linn. Soc , 42 389 -405.

Charlesworth , B. 1980 . Evolution in age structured populations . Cambridge University Press, Cambridge, U.K.

Chevillon , C. , M. Raymond, T. Guillemaud, T. Lenormand, and N. Pastuer. 1999 . Population genetics of insecticide resistance in the mosquito Culex pipens . Biol. J. Linn. Soc , 68 147 -157.

Endler , J. A. 1978 . A predator's view of animal color patterns. Evol. Biol , 11 319 -364.

Endler , J. A. 1980 . Natural selection on color patterns in Poecilia reticulata . Evolution , 34 76 -91.

Fajen , A. , and F. Breden. 1992 . Mitochondrial DNA sequence variation among natural populations of the Trinidad guppy, Poecilia reticulata . Evolution , 46 1457 -1465.

Gadgil , M. , and P. W. Bossert. 1970 . Life historical consequences of natural selection. Am. Nat , 104 1 -24.

Gingerich , P. D. 1983 . Rates of evolution: Effects of time and temporal scaling. Science , 222 159 -161.

Grant , P. R. , and B. R. Grant. 1995 . Predicting microevolutionary responses to directional selection on heritable variation. Evolution , 49 241 -251.

Grant , P. R. , and B. R. Grant. 2002 . Unpredictable evolution in a 30-year study of Darwin's finches. Science , 296 707 -711.

Groman , J. D. , and O. Pellmyr. 2000 . Rapid evolution and specialization following host colonization in a yucca moth. J. Evol. Biol , 13 223 -236.

Hendry , A. P. , and M. T. Kinnison. 1999 . The pace of modern life: Measuring rates of contemporary microevolution. Evolution , 53 1637 -1653.

Hendry , A. P. , J. K. Wenburg, P. Bentzen, E. C. Volk, and T. P. Quinn. 2000 . Rapid evolution of reproductive isolation in the wild: Evidence from introduced salmon. Science , 290 516 -518.

Irschick , D. J. , and J. B. Losos. 1998 . A comparative analysis of the ecological significance of maximal locomotor performance in Caribbean Anolis lizards. Evolution , 52 219 -226.

Irschick , D. J. , and J. B. Losos. 1999 . Do lizards avoid habitats in which performance is submaximal? The relationship between sprinting capabilities and structural habitat use in Caribbean anoles. Am. Nat , 154 293 -305.

Law , R. 1979 . Optimal life histories under age-specific predation. Am. Nat , 114 399 -417.

Lee , C. E. 1999 . Rapid and repeated invasions of fresh water by the copepod Eurytemora affinis . Evolution , 53 1423 -1434.

Lee , C. E. , and M. A. Bell. 1999 . Causes and consequences of recent freshwater invasions by saltwater animals. Trends Ecol. Evol , 14 284 -288.

Lenormand , T. , T. Guillemaud, D. Bourguet, and M. Raymond. 1998 . Appearance and sweep of a gene amplification: Adaptive response and potential for new functions in the mosquito Culex pipiens . Evolution , 52 1705 -1712.

Linnen , C. , M. Tatar, and D. E. L. Promislow. 2001 . Cultural artifacts: A comparison of senescence in natural, laboratory-adapted and artificially selected lines of Drosophila melanogaster . Evol. Ecol. Res , 3 877 -888.

Lochmiller , R. , and C. Deerenberg. 2000 . Trade-offs in evolutionary immunology: Just what is the cost of immunity? Oikos , 88 87 -98.

Losos , J. B. 1994 . Integrative studies of evolutionary ecology: Caribbean Anolis lizards as a model system. Ann. Rev. Ecol. Syst , 25 467 -493.

Losos , J. B. , D. J. Irschick, and T. W. Schoener. 1994 . Adaptation and constraint in the evolution of specialization of Bahamian Anolis lizards. Evolution , 48 1786 -1798.

Losos , J. B. , T. R. Jackman, A. Larson, K. de Queiroz, and L. Rodriquez-Schettino. 1998 . Historical contingency and determinism in replicated adaptive radiations of island lizards. Science , 279 2115 -2118.

Losos , J. B. , T. W. Schoener, and D. A. Spiller. 2004 . Predator-induced behaviour shifts and natural selection in field experimental lizard populations. Nature , 432 505 -508.

Losos , J. B. , T. W. Schoener, K. I. Warheit, and D. Creer. 2001 . Experimental studies of adaptive differentiation in Bahamian Anolis lizards. Genetica , 112 –113 399 -415.

Losos , J. B. , K. I. Warheit, and T. W. Schoener. 1997 . Adaptive differentiation following experimental island colonization in Anolis lizards. Nature , 387 70 -73.

McKenzie , J. A. , and P. Batterham. 1994 . The genetic, molecular and phenotypic consequences of selection for insecticide resistance. Trends Ecol. Evol , 9 166 -169.

Medawar , P. B. 1952 . An unsolved problem of biology . H. K. Lewis and Co. Ltd., London, U.K.

Michod , R. E. 1979 . Evolution of life histories in response to age-specific mortality factors. Am. Nat , 113 531 -550.

Miller , R. A. , J. M. Harper, R. C. Dysko, S. J. Durkee, and S. N. Austad. 2002 . Longer life spans and delayed maturation in wild-derived mice. Exp. Biol. Med , 227 500 -508.

Norris , K. , and M. Evans. 2000 . Ecological immunology: Life history trade-offs and immune defense in birds. Behav. Ecol , 11 19 -26.

Rainey , P. B. , and M. Travisano. 1998 . Adaptive radiation in a heterogeneous environment. Nature , 394 69 -72.

Reznick , D. N. 1982 . The impact of predation on life history evolution in Trinidadian guppies: The genetic components of observed life history differences. Evolution , 36 1236 -1250.

Reznick , D. N. , M. J. Butler IV, F. H. Rodd, and P. Ross. 1996 . Life history evolution in guppies ( Poecilia reticulata ). 6. Differential mortality as a mechanism for natural selection. Evolution , 50 1651 -1660.

Reznick , D. N. 1997 . Life history evolution in guppies ( Poecilia reticulata ): Guppies as a model for studying the evolutionary biology of aging. Exp. Geront , 32 245 -258.

Reznick , D. N. , M. J. Bryant, D. Roff, C. K. Ghalambor, and D. E. Ghalambor. 2004 . Effect of extrinsic mortality on the evolution of senescence in guppies. Nature , 431 1095 -1099.

Reznick , D. N. , and H. Bryga. 1987 . Life-history evolution in guppies. 1. Phenotypic and genotypic changes in an introduction experiment. Evolution , 41 1370 -1385.

Reznick , D. N. , and H. Bryga. 1996 . Life-history evolution in guppies ( Poecilia reticulata : Poeciliidae). V. Genetic basis of parallelism in life histories. Am. Nat , 147 339 -359.

Reznick , D. N. , H. Bryga, and J. A. Endler. 1990 . Experimentally induced life-history evolution in a natural population. Nature , 346 357 -359.

Reznick , D. N. , M. J. Butler, F. H. Rodd, and P. Ross. 1996 . Life history evolution in guppies (Poecilia reticulata). 6. Differential mortality as a mechanism for natural selection. Evolution , 50 1651 -1660.

Reznick , D. N. , and J. A. Endler. 1982 . The impact of predation on life history evolution in Trindadian guppies ( Poecilia reticulata ). Evolution , 36 160 -177.

Reznick , D. N. , and C. K. Ghalambor. 2001 . The population ecology of contemporary adaptations: What empirical studies reveal about the conditions that promote adaptive evolution. Genetica , 112 –113 183 -198.

Reznick , D. N. , L. Nunney, and A. Tessier. 2000 . Big houses, big cars, superfleas and the costs of reproduction. Trends Ecol. Evol , 15 421 -425.

Reznick , D. N. , F. H. Rodd, and M. Cardenas. 1996 . Life history evolution in guppies ( Poecilia reticulata ). IV. Parallelism in life-history phenotypes. Am. Nat , 147 319 -338.

Roush , R. T. , and J. A. McKenzie. 1987 . Ecological studies of insecticide and acaricide resistance. Ann. Rev. Entomol , 32 361 -380.

Schoener , T. W. , and A. Schoener. 1983 . Time to extinction of colonizing propagule of lizards increases with island size and avifaunal richness. Nature , 274 685 -687.

Sheldon , B. , and S. Verhulst. 1996 . Ecological immunology: Costly parasite defenses and trade-offs in evolutionary ecology. Trends Ecol. Evol , 11 317 -321.

Sinervo , B. , and C. M. Lively. 1996 . The rock-paper-scissors game and the evolution of alternative male strategies. Nature , 380 240 -243.

Sinervo , B. , E. Svensson, and T. Comendant. 2000 . Density cycles and an offspring quantity and quality game driven by natural selection. Nature , 406 985 -988.

Slatkin , M. 1987 . Gene flow and the geographic structure of natural populations. Science , 236 787 -792.

Stearns , S. C. 1992 . The evolution of life histories . Oxford University Press, Oxford, U.K.

Travisano , M. , and P. B. Rainey. 2000 . Studies of adaptive radiation using model microbial systems. Am. Nat , 156 S35 -S44.

Walker , D. W. , G. McColl, N. L. Jenkins, J. Harris, and G. J. Lithgow. 2000 . Evolution of lifespan in C. elegans. Nature , 405 296 -297.

Williams , E. E. 1972 . The origin of faunas. Evolution of lizard congeners in a complex island fauna: A trial analysis. Evol. Biol , 6 47 -89.

Williams , E. E. 1983 . Ecomorphs, faunas, island size, and diverse end points in island radiations of Anolis . In R. B. Huey, E. R. Pianka, and T. W. Schoener (eds.), Lizard ecology: Studies of a model organism, pp. 326–370. Harvard Univ. Press, Cambridge, Massachusetts.

Williams , G. C. 1957 . Pleiotropy, natural selection and the evolution of senescence. Evolution , 11 398 -411.

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