Resources

I’m a huge fan of ‘popular science’ books. These books, when written well, provide a great overview of a topic for the non-specialist, and can be a window into further reading. I am using popular science rather broadly here, to mean any books which do not require more than a high-school (or at most early undergraduate) background in the subject. As such, I may include books that may not, strictly speaking, be intended for a non-scientific audience. Below are some such books that I particularly liked. You can also find a list of popular science books on Michael Jennions’ website, and some ‘topicology’ books on Hanna Kokko’s website.

Ecology and Evolution

  • Improbable Destinies by Jonathan Losos - Predictability of evolution, long-term evolution
  • Beak of the finch by Jonathan Weiner - long term evolution in wild populations
  • Darwin comes to town by Menno Schilthuizen - urban evolution
  • The Loom of life by Menno Schilthuizen - Community ecology. Discusses niche models, neutral models, etc.
  • A taste for the beautiful by Michael Ryan - Mate Choice
  • Modeling Nature by Sharon Kingsland - history of modern ecology
  • An Immense World by Ed Yong - Sensory ecology
  • Braiding Sweetgrass by Robin Wall Kimmerer - Natural history, traditional knowledge. Debatable whether this should be considered science at all, but I do think its something every field ecologist should read, especially those who engage with local communities as part of their work. It helps that the writing is incredibly beautiful.

Philosophy of science/biology/ecology/evolution

  • This is Biology by Ernst Mayr - Overarching view of biology. Rather dated, but somewhat of a classic.
  • Metazoa by Peter Godfrey-Smith - Speculative book on the evolution of consciousness that I thought was quite nice.
  • What is this thing called science? by Alan Chalmers - Introduction to philosophy of science.
  • The Dialectical Biologist by Richard Levins and Richard Lewontin - Argues that the act of doing science is political and is influenced by sociopolitical biases, and advocates for a dialectical approach to biology.
  • Letters to a Young Scientist by E.O. Wilson - Inspiring series of essays directed towards young scientists.
  • Evolution and the levels of selection by Samir Okasha - Discusses multi-level selection. Rather philosophically heavy, but worth the read.
  • Idealization and the aims of science by Angela Potochnik - Discusses the role of idealization and simplification in science.

Other science

  • I Contain Multitudes by Ed Yong - How microbes affect our daily lives
  • The Gene: An Intimate History by Siddhartha Mukherjee - History of genetics
  • The Epigenetics Revolution by Nessa Carey - Fantastic introduction to epigenetics
  • Lost in Math by Sabine Hossenfelder - Critical overview of the current state of the use of mathematics in particle physics. Argues that particle physicists are too enamoured by beautiful mathematics, to the point where it is detrimental to discovery in the physical sciences.
  • The Life of the Cosmos by Lee Smolin - Proposes the ‘cosmological natural selection’ hypothesis, which states that the values of the fundamental constants that we see today is the product of a natural selection-like process occurring on universes.
  • The Oxford Book of Modern Science Writing , edited by Richard Dawkins - Collection of essays that are meant to showcase good popular science writing.
  • The Idea of the Brain by Matthew Cobb - Fantastic book discussing the history of ideas and metaphors used to describe the brain (and sometimes neurons more generally). Very interesting book, makes you think about how bound humans are to the technology around them when it comes to thinking of metaphors (Ex: Today we think of the brain as a ‘computer’, but people used to draw analogies with telegraphs and hydraulics).
  • Fermat’s last theorem by Simon Singh - Speaks about various mathematicians who worked on Fermat’s last theorem and/or developed tools that contributed to Andrew Wiles’ proof of the theorem.
  • It must be beautiful by various authors, edited by Graham Fermelo. Collection of essays about the use of mathematics in the science from a list of authors that includes Roger Penrose, John Maynard Smith, and Robert May.
  • Escape from Model Land by Erica Thompson - Mathematical modelling and its relation to real-world processes, mostly from an applied perspective (think finance, climate change, etc.).
  • Biggest ideas in the universe (Vol 1) by Sean Carroll - Brief introduction to modern classical mechanics, special relativity, and general relativity. As a person who’s comfortable with mathematics but doesn’t know physics, I found it very refreshing to read a pop sci book that does not shy away from equations but also does not assume you are familiar with physics language.

Biographies and Autobiographies of scientists

I often like reading about scientists just as much as I like reading about science. Here are some books I particularly enjoyed.

  • Naturalist by E.O. Wilson
  • A Mind at Play by Jimmy Soni (biography of Claude Shannon)
  • The Code Breaker by Walter Isaacson (biography of Jennifer Doudna)
  • Surely you’re joking, Mr. Feynman and What do you care what other people think? by Richard Feynman (sort of an autobiography, but mostly a collection of anecdotes)
  • Genius by James Gleick (biography of Richard Feynman - provides good contrast with the very biased picture Feynman paints of himself in his autobiography)
  • A feeling for the Organism by Evelyn Fox Keller (very inspiring biography of Barbara McClintock)
  • The Price of Altruism by Oren Harman (biography of George Price)
  • Nature’s Oracle by Ullica Segerstrale (biography of Bill Hamilton)

Articles on the interplay of theory and experiment in biology

I firmly believe that integrative approaches which combine theory with empirical knowledge are sorely needed in ecology and evolution. Below are some articles that discuss this idea very well (in my opinion).

Articles on mathematical biology for mathematicians

Mathematical biology today is a vibrant field, and, despite what school may try to tell you, is very mathematically rich. While there are more and more articles these days that try to convince biologists that mathematics can be interesting and useful to biology, there are far fewer articles aimed towards people with a mathematics or physics background. Below are some articles from mathematicians that paint a very rich picture of mathematical biology as a field of interest for mathematicians.

  • Vittadello and Stumpf 2022 - Open problems in mathematical biology, a paper that shows how ‘modern’ mathematical biology has several mathematically interesting open problems that draw on diverse areas of mathematics including topology, algebra, analysis, probability theory, and statistical inference.
  • Constable, Krumbeck, and Rogers 2021 - An invitation to stochastic mathematical biology, a paper that discusses various interesting open questions in mathematical biology that have to do with stochastic processes. As you will see, the questions posed are biologically interesting, and often involve notions such as random matrix theory, measure-valued branching processes, and SPDEs that are active areas of research in pure mathematics.
  • Macauley and Youngs 2020 - The Case for Algebraic Biology: from Research to Education, a brief survey of algebraic methods in modelling biological systems, both in research and in classrooms.
  • Blevins and Bassett 2020 - Topology in biology, a survey of topological ideas used in various areas of biology.
  • Borovik 2021 - A mathematician’s view of the unreasonable ineffectiveness of mathematics in biology. Eugene Wigner, an eminent physicist, once wrote a famous essay about the ‘unreasonable effectiveness of mathematics in the natural sciences’. Though Wigner said ‘science’, he really only meant ‘physics’. Soon after, Israel Gelfand, a famous mathematician, informally commented that “There is only one thing which is more unreasonable than the unreasonable effectiveness of mathematics in physics, and this is the unreasonable ineffectiveness of mathematics in biology”, but sadly passed away without elaborating on this statement. The linked article is written by a mathematician and friend of Gelfand and discusses the ‘unreasonable ineffectiveness of mathematics in biology’ from a mathematical point of view and argues that we require entirely new mathematics in order to effectively tackle biological problems. Despite the depressing title, I think the article itself is quite exciting as a source of interesting and radically new potential areas of research for mathematicians.
  • Akin 1990 - The Differential Geometry of Population Genetics and Evolutionary Games. A book chapter (appearing in Mathematical and Statistical Developments of Evolutionary Theory, Lessard Ed., Springer Dordrecht) discussing an approach to population dynamics using differential geometry. The basic idea is the following: It is well-known that population mean fitness may not be maximized over the course of evolution when natural selection is frequency-dependent. Thus, the simplistic idea of evolution as a steady ‘hill-climbing’ process towards ever-increasing mean fitness does not hold true for population with frequency-dependent selection. However, in an abstract sense, one can view the state space (usually a subset of the reals) not merely as a set, but as a Riemannian manifold. In this view, the Euclidean metric is just one of potentially many Riemannian metrics associated with the manifold, and each metric is associated with its own notion of gradients and maximization. It then turns out that under one particular choice of metric (the so-called ‘Shahshahani metric’), fitness is still maximized under the notions of maximization associated with this new metric. It bears noting that this exercise does not lead to any new biology, but instead an alternative mathematical viewpoint to try and rescue the idea of fitness maximization.
  • Champagnat, Méléard, and Tran 2022 - Multi-scale eco-evolutionary models: from individuals to populations. A talk from the 2022 International Congress of Mathematics (ICM) discussing stochastic models of finite populations of non-constant size bearing quantitative traits. These models are measure-valued branching processes and their analysis requires the use of some rather advanced tools from probability and martingale theory. You can also listen to the ICM talk here. Much of the biological consequences for evolutionary biology in relation to ideas like adaptive dynamics are covered in a 2006 paper by the same group (published in a theoretical biology journal!) - See Champagnat et al. 2006.
  • Etheridge 2011 - Some Mathematical Models from Population Genetics. A book on theoretical population genetics aimed at mathematicians who are familiar with analysis but unfamiliar with biological language and concepts.
  • ‘Physics of Life’ by the American National Physics Association. I very strongly disagree with the classification of most of the things covered in this piece as ‘physics’ or of any of the subject matter covered as ‘a field of physics’, but I include this survey here nevertheless for any stray physicists that may run into my page. This article surveys how tools first created in areas of physics such as statistical mechanics have been co-opted to study biological systems across various scales of biology. While the article is written by physicists and views these biological models as ‘areas of physics’, I urge you to notice that using a partition function (originally developed in the context of stat mech) to study ensembles of species in an ecological community is physics to the same degree that using calculus (originally developed in the context of Newtonian mechanics) to model Lotka-Volterra communities is physics :)

Resources for academia: technical skills

Data visualization

Coding

Reading, writing, and presentation

Resources for academia: Applications and advice

Other lists like this one

PhD Stuff

Applying to PhD programs in the USA

Living the grad student life (much of this is in the USA context)

PhD preview programs that will help you apply to PhD programs in the US

Drafting emails

Writing emails to potential advisors

Requesting a recommendation letter

Miscellaneous

  • An EEB napkin, my attempt at making a version of Evan Chen’s infintely large napkin for theoretical ecology and evolutionary biology.
  • Lecture notes that I took during my education at IISER Pune. Currently has notes on NLD (from Strogatz), genetics (chromosome mapping, transposons, genetic screens, forward & backward genetics techniques, sequencing techniques, CRISPR-Cas), neurobiology (mostly cellular stuff; Hodgkin-Huxley and its precursor models), statistical inference (sufficient statistics, hypothesis testing, confidence intervals, etc. from a math view. No prerequisites), graph theory (basic definitions, Eulerian and Hamiltonian graphs/paths/cycles, matching and perfect matching, vertex and edge cuts, max flow-min cut, intro to graph coloring, intro to Ramsey theory and extremal graph theory) , statistical mechanics (Covers all of Reif’s intro textbook, culminating in statistically deriving the laws of thermodynamics. No prerequisites), measure theory (abstract measure spaces, lebesgue integration, product measures and Fubini’s theorem, Lp spaces, Radon-Nikodym theorem, differentiation of measures; No prerequisites. Important results are presented in a separate document in case you don’t care for proofs), probability (Markov chains, intro to measure theoretic probability, martingale theory; Knowing measure theory is helpful for the second half, but all necessary results are introduced), stochastic processes (Markov chains ‘properly’, Brownian motion, stochastic calculus, SDEs; This needs some measure theory and probability, important results are presented in the first few pages) and PDEs (transport eqn, method of characteristics, Poisson eqn and associated results for harmonic functions, heat eqn, wave eqn, intro to Fourier transforms, their properties, and how to use them to solve PDEs; Notions such as Lp norms are used regularly, so familiarity with basic measure-theoretic notions will be useful. Some proofs here and there need actual results from measure theory).
  • Applied Analysis, a textbook by John Hunter and Bruno Nachtergaele that covers various topics from Analysis that are relevant for (mathematically oriented) modellers (Ex: Function spaces, Linear operators, Fourier transform, Measure spaces, calculus of variations)
  • Dynamic Ecology, a blog by Jeremy Fox. Discusses various aspects of ecology, evolution, modeling, etc.
  • Major Revisions, an ecology podcast by working ecologists
  • A guide to metaphors in ecology and evolution
  • Various notions of stability in ecology
  • Fantastic interview of John Maynard Smith