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EPHE Core Winter 2010

EPHE Core Schedule of Lectures and Assignments

ECL 298-008 (40087)

Time: TR 12:10-1:30
Room: Storer 2342


Jan 5 – The unification of the social sciences (Richerson) - Read: Gintis Unity BBS

Economic Approaches to Human Behavior (Sanchirico/Springborn/Lin)

Jan 7 – Theory of consumer/firm, overview of economics and fields (Sanchirico)

Jan 12 – Public Goods and Externalities (Sanchirico/Lin)

Jan 14 – Dynamic Resource Models (Lin)

Jan 19 – Decision-making under uncertainty (Springborn)

Cultural Evolution (Richerson/McElreath)

Jan 21 – The nature of culture (Richerson)

Jan 26 – Modeling cultural evolution (Richerson/McElreath)

Jan 28 – Analyzing cultural evolution (Richerson/McElreath)

People and Conservation (Darwent/Borgerhoff Mulder)

Feb 2 – Many roads to conservation (Borgerhoff Mulder)

Feb 4 – (Darwent)

Feb 9 – TBD

Feb 11 – TBD

Cultural Ecology/Political Ecology (Orlove/Winterhalder)

Feb 16

Feb 18

Feb 23

Feb 25

Environmental Policy and Politics (Lubell)

Mar 2 – Policy Tools

Mar 4 – Overview of US Environmental Laws

Mar 9 – Theories of the Policy Process

Mar 11 – Frontiers in Policy Research

Adrian Bell's page

I am a 6th (and final) year student in the Graduate Group in Ecology at UC Davis. My advisors are Pete Richerson and Richard McElreath. Below is my list of contributions. You can see my full profile by following the link below.


Bell, Adrian V., Peter J. Richerson, and Richard McElreath. 2009. “Culture Rather than Genes Provides Greater Scope for the Evolution of Large-Scale Human Prosociality” Proceedings of the National Academy of Sciences 106(42):17671-17674.

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Monique Borgerhoff Mulder, Samuel Bowles, Tom Hertz, Adrian Bell, et al.. “Intergenerational Wealth Transmission and the Dynamics of Inequality in Small-Scale Societies” Science 326 (2009) 682-688.

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Bell, Adrian V. 2010. Why Cultural and Genetic Group Selection are Unequal Partners in the Evolution of Human Behavior”Communicative and Integrative Biology 3(2): 159-161.

Lybbert, Travis, and Adrian V. Bell. 2010. “Stochastic Benefit Streams, Learning and Technology Diffusion: Why Drought Tolerance is not the new Bt” in press at AgBioForum 13(1): 13-24. With commentary in Nature Biotechnology 28: 553-554 (2010).

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Mary K. Shenk, Monique Borgerhoff Mulder, Jan Beise, Gregory Clark, William Irons, Donna Leonetti, Bobbi S. Low, Samuel Bowles, Tom Hertz, Adrian Bell, and Patrizio Piraino. 2010. “Intergenerational Wealth Transmission among Agriculturalists: Foundations of Agrarian Inequality.” Current Anthropology 51(1): 65-83

Smith, E.A, Hill, K., Marlowe, F., Nolin, D. Wiessner, P, Gurven, M. Bowles, S., Borgerhoff Mulder, M., Hertz, T., and Bell, A. 2010. Wealth Transmission and Inequality Among Hunter-Gatherers. Current Anthropology 51(1): 19-34

Gurven, M., Borgerhoff Mulder, M., Hooper, P.L., Kaplan, H., Quinlan, R., Sear, R., Schniter, E., von Rueden, C., Bowles, S., Hertz, T., and A. Bell (2010) Domestication alone does not lead to inequality: Intergenerational wealth transmission among horticulturalists. Current Anthropology 51(1): 49-64

Borgerhoff Mulder, M., Fazzio, I., Irons, W., McElreath, R., Bowles, S., Bell, A., Hertz, T and L. Hazzah (2010). Pastoralism and Wealth Inequality: Revisiting an Old Question. Current Anthropology 51(1): 35-48.

Bell, Adrian V., Russell B. Rader, Steven L. Peck, & Andrew Sih. “The positive effects of negative interactions: can avoidance of competitors or predators increase resource sampling by prey?” Theoretical Population Biology 76 (2009) 52-58.

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McElreath, R., A. Bell, C. Efferson, M. Lubell, P. Richerson, and T. Waring. 2008. Beyond existence and aiming outside the laboratory: Estimating frequency-dependent and payoff-biased social learning strategies. Philosophical Transactions of the Royal Society B 363:3515-3528.

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Bell, A. V., and P. J. Richerson. 2008. Charles J. Lumsden and Edward O. Wilson, Genes, Mind, and Culture: 25th Anniversary Edition. Journal of Bioeconomics 10(3), p.307

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Bell, Adrian V., & Mark Belk. “Diet of the leatherside chub, Snyderichthys copei, in the fall” The Western North American Naturalist 64(3), 2004, pp. 413-416

Timothy Waring


    I am intensely fascinated by biological and cultural evolution, the fundamental difference between the two, and the implications for the interaction of the two systems.  I study how ecological and biophysical factors exert selective forces on human institutions, and how the study of cultural evolution might aid in the search for sustainable (and durable) institutions.

PhD Research

    I am currently analyzing and writing my dissertation in Human Ecology at U.C. Davis.  My research  tests the influence of ethnic/caste diversity and hierarchy on a traditional cooperative irrigation system in southern India.  A sizable literature demonstrates that ethnic diversity negatively effects public goods provision in realms such as public schooling, policing, and environmental management.  This literature might overlook the importance of inter-ethnic relationships in determining cooperative regimes within societies.  I use a range of methods, from  traditional ethnography, to surveys, to quantitative experimental games to measure human behavior.

Recent Research

    I study the interaction between cultural processes and environmental conditions in Southern India. Because cooperation is a key component of sustainable resource management, I measured social norms of fairness and sharing in a small group of day laborers in Tamil Nadu to measure the strength of three social preferences: self-interest, equality, and social efficiency. The results suggest that people have preferences for how to distribute wealth that go beyond classical economic utility maximization, and include concern for how others are treated. Future research of this type will be used to measure cooperation between social groups as a component of successful sustainable environmental management. This work also will contribute empirical evidence to ongoing discussions about the nature of human social preferences.

Web Pages


Previous Research

Water use and water quality in Bardiya National Park - Nepal

Spatially explicit ecological simulation of the Everglades - SFWMD

Social learning and environmental fluctuation - UC Davis

Social norms of sharing in day laborer population - Kodaikanal, India

Baryplot R package

Barycentric Coordinates

The triangular phase plots often seen in game theoretic publications (called ternary plots, de Finetti diagrams, simplex, etc.) are plots in barycentric coordinates. This coordinate system is handy, because it plots three components which sum to a constant. In game theory, the three things are three strategies, and their frequencies must sum to one.

Baryplot Library for R

R is an open source framework for doing and vizualizing statistics. It is a full-featured programming language, complete with vector-based drawing. I have written a library of functions that allows one to easily plot vector-based barycentric game theoretic plots. Since the resulting plots are vector-based, they can be scaled, edited, and printed with no loss of quality. And since it is all wrapped in R, complex games can be programmed and passed to the plots as parameters.

To use this library, first you will need to download and install R. R is freely available for Windows, Mac (OS 9 and OS X), and Linux.

Now execute the two lines below within R, to install the package from the internet:



Using baryplot

Once the library is installed, you load it by typing "library(baryplot)". You can get online help for its functions using "library( help=baryplot )". Use "?functionname" to get help on an individual function. For example, "?bary.sim".

The commands below produce the plot below.


Interactive plotting

Try typing...


...then click inside the triangle.

See the help for ("?" at the R prompt) for optional parameters it can take.

Plotting a new game

To plot a custom game, you just need to write a short function that returns payoffs for each of the three strategies. If you type "" at the R prompt, you'll see the code for the game that is plotted above:

function (p, q, r, v = 2, c = 3, w0 = 5)
w1 <- (p + q) * (v - c)/2 + r * v + w0
w2 <- p * (v - c)/2 + (1 - p) * v/2 + w0
w3 <- (1 - p) * v/2 + w0
c(w1, w2, w3)

p, q, and r are the frequencies of each strategy. The baryplot library provides those to this function. You just need to write the expressions that use those frequencies to compute fitness values w1, w2, and w3. Here's a template: <- function(p, q, r, w0 = 10) {
w1 <- p * 0 + q * 1 + r * (-1) + w0
w2 <- p * (-1) + q * 0 + r * 1 + w0
w3 <- p * 1 + q * (-1) + r * 0 + w0

If you paste that code into R, you can then plot the game by adding a parameter to the simulation call. See the help for bary.sim (type ?bary.sim) for details. The simplest call will look like: