Welcome to EEB 390 - Evolutionary Biology

Welcome to EEB 390 - Evolutionary Biology

Topic 1. Lectures 1-2. Basic Concepts of Evolutionary Biology

We will start by considering 30 basic concepts of Evolutionary Biology. There will be no hard facts to remember today or in the next lecture.

So, relax - but pay attention!

Naturally, the first question we need to address is this:

What is Evolutionary Biology?

You may expect Evolutionary Biology to study evolution of life, and this is correct, as a first approximation.

Thus, the very first concept we need to introduce is evolution of life.

What is Evolution of life?

Evolutio = unrolling (Latin).

As time flows, organisms which currently represent a lineage, a succession of organisms connected to each other by ancestor-descendent relationships, keep changing and deviate more and more from the original ancestors.

Darwin called this phenomenon descent with modification, now we call it evolution.

Why is time flowing upwards on this picture?

Strictly speaking, individual organisms do not evolve - only long-lasting lineages of organisms could evolve.

Of course, natural changes of organisms in a lineage could only be evolutionary (slow and gradual): a daughter must always be very similar to her mother.

Modern life is complex and diverse.

The central claim of Evolutionary Biology is that modern life is a product of long evolution in the past.

Thus, Evolutionary Biology has two basic tasks - to explain diversity and complexity of life.

Evolutionary Biology is a science that studies origin of living beings with new qualities.

Any substantial changes of life is a fair game for evolutionary biology.

30 Basic Concepts of Evolutionary Biology

1. Anagenesis, Cladogenesis.

2. Phase space, Determinism, Space of genotypes.

3. Levels of organization, Phenotype, Trait, Fitness, Adaptation.

4. Mutation, Variation, Population, Selection, Allele replacement.

5. Fitness landscape.

6. Similarity, Relatedness, Compatibility, Connectedness.

7. Clade, Species.

8. Complexity, Optimality, Evolvability, Designability.

9. Stochasticity, Random drift.

10. Microevolution, Macroevolution.

Bad news: you really need to understand all these difficult concepts.

Good news: you probably understand most of them already.


To explain the origin of modern biodiversity, Evolutionary biology makes two claims - Weak Claim and Strong Claim - about life in the past.

Weak Claim: if we take a modern species (form of life), and trace its lineage back in time, we will encounter organisms that deviate more and more from this species.

This claim may seem weird - elephants do not produce bears.

We need to understand why biologists universally accept these weird claims.

Thus, in lectures 3-6 we will consider indirect evidence for past evolution.

Strong Claim: if we take several modern species, and trace their lineages back in time, we will see them merging one-by-one until, at some remote moment, the only one lineage remains. Thus, all modern species have Common ancestry.

This may seem even more weird - there are no intermediate forms between humans and flies.

In other words, the Weak Claim asserts that Anagenesis (changes in one lineage) happened,

and the Strong Claim asserts that Cladogenesis (splitting of an evolving lineage) happened.

These two evolutionary processes are responsible for the origin of complexity and diversity of life.


When an object can exist in many different states, it helps to think of its Phase space which consists of all these states .

Phase, state, and configurational space are synonyms.

The concept of phase space permeates all natural sciences.

Changes of the object correspond to movements of the point which represents its current state within the phase space.

If these changes are gradual (evolution), the movement does not include any instant leaps.

Let us consider four examples of phase spaces.

Phases of water in the two-dimensionalEuclidian temperature-pressure phase space.

Solid, liquid, and gaseous are three phases of matter.

Can you think of a one-dimensional phase space?

What is the phase space of a pendulum?

Shapes of fly wings reside in an infinite-dimensional phase space of continuous functions.

Still, a wing can be, as a good approximation, described by a finite number of parameters: length, width, and, say, two parameters characterizing its shape.

Who needs more dimensions to describe a human being - a tailor or a surgeon?

Natural sciences is a struggle to describe complex objects in a manageable way.

Phase space of chess

Initial position All possible movesby white

Impossible position

Q: How many positions and how many games are possible?

A: Way more than the number of electrons in the Universe.

The numbers of positions and games are about as large as the numbers of sequences and of evolutionary trajectories of a short protein.

Phase space of English texts

We cannot convert Hamlet into Pride and Prejudice by small editorial changes, in such a way that all the intermediate texts are meaningful. Or can we?

So, how can a prokaryote genome be transformed into a human genome, by accumulating a lot of (mostly) small mutations one-by-one, and without becoming meaningless along the way?

The ultimate goal of Evolutionary Biology is to answer this question - and we are still a very long way from acheiving it.

In some simple cases, we may assume that movements with the phase space are deterministic.

Determinism: assumption that the current state of an object predetermines its changes in the future. A deterministic process is predictable and reproducible.

Example: radioactive decay is a (macroscopically) deterministic process: knowing the current number of radioactive atoms, we can predict (approximately!) this number for any moment in the future, and infer it for any moment in the past.

One-dimensional phase space of the number N of radioactive atoms. Rate of N as a function of N ( is the constant of decay): dN/dt = -N.

Because N declines at rate proportional to it current value, N is an exponential function of time t: N(t) = N0e-t.

One-dimensional phase space of the frequency [A] of an advantageous allele A. Rate of [A] as a function of [A] (s is selection coefficient):

d[A]/dt = s[A](1-[A]) (blue line).

Natural selection is a macroscopically deterministic process, due to the same reasons as in the case of radioactive decay.

Some aspects of evolution can also be viewed as a deterministic process.

Thus, the key equation of evolution theory is also a differential equation!

Red lines: [A] as functionof time t:

[A](t) = 1/(1+((1-[A]0)/[A]0)e-st)

Evolution of life unfolds within the Space of genotypes - because an organism is, first of all, characterized by its genotype.

To call the number of all possible genotypes that are not longer than ours, 43,000,000,000 = 101,600,000,000 astronomical is a huge understatement. Of course, the vast majority of these sequences are garbage - and still evolution must somehow navigate its way through the space of genotypes.

Space of genotypesis L-dimensional,where L is the lengthof the longest genotype.

How long is thehuman genome?

Genome =consensusof genotypes


Levels of organization: sequences, molecules, cells, organisms, populations, ecosystems.

The idea is simple:

This is an interaction between organisms (individuals) - not between cells or molecules.

When possible, we will try to consider evolution at different levels of organization independently. Still, evolution of genotypes is behind it all.

Phenotype: any description of life at any level (usually, the term is not applied to sequences, populations, or ecosystems).

Life has to rebuild itself from the ground up every generation.

Genotype -> phenotype maps are a key subject in biology:

mglsdgewql vlnvwgkvea dipghgqevlirlfkghpet lekfdkfkhl ksedemkasedlkkhgatvl talggilkkk ghheaeikplaqshatkhki pvkylefise ciiqvlqskhpgdfgadaqg amnkalelfr kdmasnykelgfqg

Trait is a part of description of the phenotype. How to subdivide a phenotype into traits? Informally, we want traits to:

1) Work within the organism as independently as possible,2) Vary between the organisms as independently as possible,3) Provide the most compact possible description of variation,4) Make sure that descriptions of parents and offspring are similar.

This common-sense approach will be sufficient. For example:Hs 1 MALWMRLLPLLALLALWGPDPAAAFVNQHLCGSHLVEALYLVCGERGFFYTPKTRREAED 60Pt 1 MALWMRLLPLLVLLALWGPDPASAFVNQHLCGSHLVEALYLVCGERGFFYTPKTRREAED 60Cf 1 MALWMRLLPLLALLALWAPAPTRAFVNQHLCGSHLVEALYLVCGERGFFYTPKARREVED 60Ss 1 MALWTRLLPLLALLALWAPAPAQAFVNQHLCGSHLVEALYLVCGERGFFYTPKARREAEN 60Bt 1 MALWTRLRPLLALLALWPPPPARAFVNQHLCGSHLVEALYLVCGERGFFYTPKARREVEG 60

Hs 61 LQVGQVELGGGPGAGSLQPLALEGSLQKRGIVEQCCTSICSLYQLENYCN 110Pt 61 LQVGQVELGGGPGAGSLQPLALEGSLQKRGIVEQCCTSICSLYQLENYCN 110Cf 61 LQVRDVELAGAPGEGGLQPLALEGALQKRGIVEQCCTSICSLYQLENYCN 110Ss 61 PQAGAVELGGGLGGLQALALEGPPQKRGIVEQCCTSICSLYQLENYCNOO 108Ss 61 PQAGAVELGGG--LGGLQALALEGPPQKRGIVEQCCTSICSLYQLENYCN 108Bt 61 PQVGALELAGGPGAGGLEGPPQKRGIVEQCCASVCSLYQLENYCNOOOOO 105Bt 61 PQVGALELAGGPGAGGL-----EGPPQKRGIVEQCCASVCSLYQLENYCN 105

Alignment of preproinsulin sequences from 5 mammals.

Before we define sequence traits, sequences should be aligned. Then, the i-th trait describes the amino acid (including "-") which occupies the i-th position within the alignment.

Fitness: a trait of the complete phenotype of an organism which describes the efficiency of its reproduction.

Simplistically, (absolute) fitness is the total number of offspring.

Function (biological): any process, within the organism, which contributes to its reproduction.

Adaptation (noun): any part of the phenotype which performs a function.

What are the functionsof human heart, and whatadaptations are responsiblefor performing them?

An adaptation can be general, being useful under a wide range of environments (like heart).

Alternatively, an adaptation may work only under a very specific environment.

Mullerian mimicry, mutualistic resemblance between unpalatable species, involving Heliconius melpomene, Heliconius erato, and their comimics in Eastern Peru. On the top line are H. melpomene (left) and H. erato (right) from the upper Huallaga. Their pattern switches to join a "rayed" mimicry ring in the lower Huallaga, where a similar rayed pattern was adopted by 10 different unpalatable species. Thus, the rayed pattern is adaptive only in one locality.


Mutation: any change in the DNA sequence due to unavoidable errors in its replication and in the repair of its damages.

TCATAGA > TCAGAGA (substitution, transversion)

TCATAGA > TCAAGA (deletion of 1 nucleotide)

Variation: any differences, genotypic or phenotypic, between organisms from some set.

Dominant allele withincomplete penetrance?

Population: a set of organisms that represent competing lineages, such that expansion of one lineage would lead to decline of others. Members of the same population live together (more or less) and usually can interbreed (if sexual).

Every organism belongs to a population. Why?

There are at least two reasons: 1) organisms are smaller than their environments, 2) a lone lineage would soon go extinct.

Selection (natural selection): differential reproduction of individuals within a population - an unavoidable consequence of variation in fitness.

It is convenient to reserve the term "selection" only for those situations when different genotypes (or phenotypes) confer different (average) fitnesses.

The outcome of selection depends only on relative fitnesses of genotypes.

If we think in terms of populations, the concept of selection is obvious: the winner is the one who runs faster.

Allele replacement: changes of frequencies of alleles (genes) within the population, resulting in one allele replacing all other alleles at the locus. Selection-driven allele replacement is the key process in Darwinian evolution.

Increase, with time, of the frequency of the fittest allele.

How many selection-driven allele replacements did it take to convert apes into humans? Definitely less than 30,000,000 - and may be just 300?

The Darwinian mechanism of evolution, by mutation and selection, is very wasteful. Lamarckian evolution would be more efficient .

Also, selection is greedy - it cannot have any foresight.

So, how could it possibly produce any good outcomes?

Apparently, a greedy algorithm can work! Still, it seems likely that many potentially nice phenotypes can never be produced by Darwinian evolution.

Important notes about this course:

1) STUDY POSTED MATERIALS BEFORE EACH LECTURE. I HAVE NO CHOICE BUT TO GO FAST - I WANT TO TEACH YOU SOMETHING.

2) In the Syllabus, you will find a list of 40 questions, which cover the whole course. All tests will be based only on these questions.

3) There will be a one-question quiz at the end of each lecture, due before the beginning of the following lecture. You are ENCOURAGED to discuss answers with your peers, but please write them independently!

4) I WANT to see you in my office hours (or contact me if you need to talk at a different time - [email protected]).

Disclaimer:

You may have religious beliefs that make it impossible to accept past evolution of life as a fact. Relax and fear not - my job is to teach you biology, and not to indoctrinate you in the matters of faith. I will try to make sure that you understand and remember scientific concepts, data, and reasoning. If you succed in this, but still believe that the Earth was created 6,000 years ago (and, perhaps, that Prof. Kondrashov, as an "evolutionist", will end up in Hell), this is none of my business.

Personally, I think that denying well-established facts for the sake of religion - or anything else - is ridiculous and sad. However, I grew up under Communism and absolutely hate it when an authority imposes its views by coercion.

Quiz - due when you enter the room for the next lecture:

What are the differences between Lamarckian and Darwinian mechanisms of evolution? Why the superior Lamarckian mechanism is not working in nature? Do you think it would be possible to distinguish the outcomes of Lamarckian and Darwinian evolution?

Hint: these are open-ended questions. Show your reasoning, give some examples, and everything will be OK.


Fitness is a function (mathematical) in the space of genotypes. Fitness landscape is a graph of this function. In other words, fitness landscape (= adaptive topography), is a genotype > fitness map.

Fitness landscapes is the best "mental language" for thinking about evolution. Still, it is a difficult concept!

The "ultimate" fitness landscape exists over the >3,000,000,000-dimensional space of complete genotypes. Obviously, it cannot be drawn! Thus, it helps to consider fitness landscapes over spaces of partial genotypes or phenotypes. Let us first assume that fitness depends only on 1 or 2 traits.

Fitness of the majority of possible genotypes is 0.

If fitness is below 1, the lineage will go extinct.

There are fitness maxima (peaks) separated by valleys.

Fitness landscape over two-dimensional phase space.

Because selection tries to increase fitness, maxima on the fitness landscape are of particular importance. Nothing new appears with more than two dimensions.

A local maximum (peak) on the fitness landscape is surrounded by its slopes, which constitute its domain of attraction. A lineage under selection will climb the peak in whose domain of attraction it was located initially, and stay on it forever. Thus, any fitness maximum is a trap for an evolving lineage.

Thus, key properties of fitness landscapes imply that greedy Darwinian evolution must be subject to historical constraints. Indeed, such constraints are everywhere. For example, superficially similar sharks, ichthyosaurs, and dolphins retain a lot of features that define them as fishes, reptiles, and mammals, respectively.

Still, this simple analysis is definitely not the whole story, because of 3 paradoxes:

1) peaks on a generic fitness landscape are all of different heights, but the mean absolute fitness of any lineage must be very close to 1.

2) evolution keeps going on for over 3.5 billion years, without settling on any peak.

3) A lineage sometimes splits into two, instead of always climbing up as a unit.

These paradoxes can be resolved if we remember that fitness landscapes are not invariant, but depend on the environment. In other words, we have to consider not just one fitness landscape, but a family of them, each corresponding to one of many possible sets of environmental conditions.

Resolution of paradox 1:

If the height of an occupied fitness peak exceeds one, the size of the population which occupies it increases, eventually causing the peak to reach the equilibrium height of one - the fitness landscape bends locally under the weight of the population.


The environment may affect not only the heights, but also the locations of peaks. This can lead to never-ending evolution if the peak occupied by a population keeps moving. The population will follow, with some lag.


If two populations occupying the same position within the space of genotypes experience different fitness landscapes, their evolution can proceed along completely different paths. This can happen, for example, if the two populations live in different locations and under different environments.

Instead of the family of all possible fitness landscapes, we may consider only fitness peaks, and plot their locations under all possible environments. When the environment, and the fitness landscape, changes slightly, a peak usually responds by moving a little. However, occasionally a peak can disappear or appear out of nothing. Still rarer, one peak splits into two, or two peaks merge into one. Thus, all possible locations of fitness peaks form a system of connected and branching ridges.

Or we can draw a more inclusive picture, and show not just peaks but all genotype which possess non-zero fitnesses under some environments. Such genotypes are a small minority, as most of possible genotypes are garbage. Still, evolution can occur only if fit genotypes form long enough continuous paths within the space of genotypes.

Try to master the language of fitness landscapes - it is the key to understanding evolution.

Complete fitness landscapes are unknown. Think of immense, highly complex fitness landscapes mostly hidden in the darkness of non-existence, with only tiny spots on them visible, each illuminated by a population.


To comprehend the enormous diversity of life, the following 4 concepts, each applicable to just a pair of individuals, are very useful.

Similarity of two individuals can refer to their genotypes or phenotypes.

Genotypes of a human (Homo sapiens) and a chimpanzee (Pan troglodytes) are98.7% similar, if we count only nucleotide substitutions, or ~95% similar,if we also count gaps with their lengths:

ATACGATCGATACGATCGATCGAAGCATGC---GTGTGATC ACACGA----------CGATCGATGCATGCACAGTGTGATC

Relatedness of two individuals is the time (or a number of generations) which lapsed since their last common ancestor.

The last common ancestor of a human and a chimpanzee lived ~6 million years, or ~300,000 generations, ago.

http://www.freedesktopwallpapers.ru/animals/images/chimpanzee.jpg

Aquilegia formosa Aquilegia pubescens

Two "species", A. formosa and A. pubescens, are connected by a wide variety of intermediate individuals.

Common ancestry implies that any two individuals, however dissimilar, are connected if we take past life into account.

Connectedness of two individuals describes whether their genotypes and phenotypes are connected by a continuous chain of genotypes and phenotypes of other currently existing individuals.

Two fit organisms may, nevertheless, be incompatible to each other, like horses and donkeys.

Compatibility of two individuals describes whether genotypes consisting of assortments of corresponding segments from their genotypes would be OK.

In contrast, Africans and Europeans are compatible.

Two very similar individuals must also be closely related, compatible, and connected. Still, there is no 1:1 correspondence between these four characteristics of pairs of individuals.

The hippopotamus is more similar, at least at the level of phenotypes, to the pig, but is more closely related to the dolphin.

Sometimes, rather different genotypes are, nevertheless, connected to each other by a continuous chain of currently-living genotypes.

A ring of forms of greenish warbler, Phylloscopus trochiloides. The two extreme forms, blue and red, live together in Central Siberia without much interbreeding. Still, these two forms are connected, in the space of genotypes, by a continuum of intermediate forms, whose ranges go around the Tibetan Plateau.

The opposite pattern: disconnected forms may yet be compatible. Rhododendron catawbiense (Eastern North America, left) and R. fortunei (China, right) are distinct "species", with no natural intermediates. Nevertheless, they are fully compatible, and produce fertile hybrids (center).

Concepts of similarity, relatedness, connectedness, and compatibility provide us with the language that is necessary to think about the structure of biodiversity.

7. Clade, Species. Now we are ready to address the structure of biodiversity. Here, the two most important concepts are clade, which is relevant to relatedness, and species, which is relevant to compatibility.

Clade: any complete branch of a phylogenetic tree, a set of all descendants of a particular common ancestor. Every two members of a clade are more tightly related to each other than any one of them to any non-member.

Examples of clades

Species: a set of individuals that are all compatible to each other.

All modern humans belong to the same species, Homo sapiens, perhaps to the exclusion of Pan troglodytus.

Life is not always that simple, and we will encounter many gray areas later.


Complexity is another general property - and wonder - of life. To understand the origin of complex phenotypes is another great goal of Evolutionary Biology. This goal is even more elusive than understanding the origin of biodiversity.

Both goals were clear to Darwin. The title of his most famous book refers to the origin of biodiversity, but he explicitly described the origin of complexity as the most mysterious facet of evolution.

"To suppose that the eye, with all its inimitable contrivances for adjusting the focus to different distances, for admitting different amounts of light, and for the correction of spherical and chromatic aberration, could have been formed by natural selection, seems, I freely confess, absurd in the highest possible degree." (Darwin, "The Origin of Species", 1859, Chapter 6).

Complexity is not easy to define. Still, a phenotype is complex if it:

1) consists of many interacting parts, 2) requires a long description, so that its phase space has many dimensions, 3) is fragile, so that even a small change can alter its properties radically.

We encounter staggering complexity at all levels of organization of life. Still, sequences and populations are simpler than molecules, cells, and organisms.

In order to think about evolution of complex phenotypes, the following 3 concepts are of great help.

Optimality: a phenotype is optimal if it performs its function better than any other feasible phenotype. Greedy evolution can hardly produce optimal complex phenotypes - it does not permit radical redesigning. Human eye, although marvelous, is a striking example of suboptimality.

Evolvability: a phenotype is evolvable if it can be changed a little, without losing its function. Currently, experimental studies of evolvability are possible only at a very limited scale.

A: Five amino acids of isopropylmalate dehydrogenase that cause it to preferentially bound NAD (ignore anomalous Arg341).

B: Five amino acid replacements which convert NAD-binding enzyme into NADP-binding enzyme.

Designability: a phenotype is designable if greedy evolution can arrive to it from a wide range of other phenotypes.

How designable are natural adaptations?

Somehow, evolution managed to arrive to the human eye, starting from very simple photoreceptors and gradually perfecting them.

Euglena is a protist with a distinct eyespot. Euglena displays phototaxis - a reaction to light.

The "cross-eyed" flatworm Dugesia has two eyespots composed of cells full of photosensitive pigments. These eyespots allow Dugesia to react to light.


Determinism is simple and neat, but it is not the whole story.

Stochasticity: a process is stochastic if it is unpredictable and irreproducible.

Is Nature inherently deterministic or stochastic? Einstein believed in determinism ("God does not play dice"), but, apparently, he was wrong.

if a population simply climbs on the fitness landscape, it will always arrive to the same peak, starting from a particular initial state. However, in reality evolution is a stochastic process, due to several reasons:

1) mutation is a quantum phenomenon and, thus, is inherently stochastic, 2) environments and initial conditions are irreproducible. 3) reproduction of an individual is unpredictable, for all practical purposes, 4) populations are too small to mask this elementary stochasticity.

Random drift refers to stochastic fluctuations of allele frequencies in the population, due to reasons 3) and 4).

Because the number of individuals in any population is smaller than the number of atoms in any sample, determinism is a poorer (but still often useful) approximation for population processes than for radioactive decay.

Rock pocket mice, are generally light-colored and live on light-colored rocks. However, some of their populations live on dark lava, and they acquire dark coat color. In different places, dark coat colors evolved by completely different genetic mechanisms.

Because of its stochasticity, evolution, facing essentially the same situation on several occasions, usually takes a different course each time.


The most important pattern in biodiversity is that in the space of genotypes (or phenotypes) it consists of clumps of similar individuals. This is rather similar to stars, most of which are parts of galaxies, within the physical space.

Two-scale structure of biodiversity: every organism belongs to a more or less distinct group (cluster, population, form of life) of very similar organisms.

Two-scale structure of visible matter: a majority of stars are organized in galaxies.

Macroevolution is obviously important - it describes origin of novel organisms.

Why do we care about Microevolution? Because Macroevolution occurs through natural selection of advantageous variants within populations. In other words, Microevolution drives Macroevolution.

An allele replacement is an interface between Microevolution and Macroevolution.

This two-scale structure of biodiversity leads to two distinct scales in the evolution of life.

Microevolution - small changes, at the scale of differences between members of the same population.

Macroevolution - profound changes, at the scale of differences between different forms of life.

Time scales of Micro- and Macroevolution.

We just reviewed

30 Basic Concepts of Evolutionary Biology







7. Clade, Species.




Are they really that difficult?

Q: What motivates the overall structure of this course?

A: The structure of modern evolutionary biology, which consists of 3 parts:

II) Studies of Microevolution. Successful since XX century.

III) Studies of Macroevolution. Still in their infancy, will flourish in XXI century.

Data on past evolution remain our key source of information on how Macroevolution works and, moreover, the main reason to believe thatMacroevolution is, indeed, possible.

Microevolution can be understood by combining Darwinian selection with Mendelian genetics ("evolutionary synthesis").

We still do not understand Macroevolution well. There are many useful generalizations, but only very fragmented theory.

?

I) Studies of past evolution. Successful since XIX century.

Structure of this course in more detail(see posted Syllabus for even more detail)

1-2. Basic concepts of evolutionary biology

I) PAST EVOLUTION3-6. Evidence for past evolution of life7. Reconstructing the course of past evolution8. Earth and fossils9-10. History of life on Earth11. Recent history of the Homo sapiens lineage12-13. Generalizations emerging from past evolution14. Evolution while you are watching

II) MICROEVOLUTION15-16. Populations and tools for studying them17. Within-population variation18. Mutation19. Natural selection20. Sex, population structure, and random drift21. Actions of positive, negative, and balancing selection22. Microevolutionary mechanisms of Macroevolution23. Species and speciation

III) MACROEVOLUTION24. Macroevolution of genomes25 Macroevolution of complex phenotypes26. Macroevolution of populations27. Macroevolution of ecosystems

IV) EPILOGUE28. Implications of evolutionary biology outside natural sciences

I hope that you will find this structure sensible.

Quiz - due when you enter the room for the next lecture:

What fundamental properties of nature make evolution unpredictable, and to what extent can we ignore this unpredictability?

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Welcome to EEB 390 - Evolutionary Biology