Human Capital Vol. 1, N. 1: First issue of a new journal

University of Chicago Journals has recently published the first issue of the new journal - Human Capital . This journal is based on a series of theoretical developments in economics beginning about 40 years ago leading to what today is called human capital theory. While it dates back to some classic theorists it is probably most closely associated with economists Gary Becker and Theodore Schultz. Students of human evolution should be familiar with the concept from its role in embodied capital theory, which has been used by Hilly Kaplan and colleagues to explain the coevolution of intelligence, long lifespan, dependent offspring, and complex foraging niche that has characterized primate diversification in general and especially the evolution of the human life course and adaptive niche (a pdf of one of the papers on this can be found here).

All of the articles in this inaugural issue look really interesting and blog worthy, so I'm just going to post titles and abstracts so that they are on your radar. It looks like it should be a really interesting journal to watch and I look forward to taking in some of these papers during vacation.
The first paper is by Isaac Ehrlich and Kevin M. Murphy and explains why a seperate journal of human capital is necessary. It gives a nice explanation for the rationale of human capital theory and its historical development.

The rest of the papers in the journal are as follows:

Education and Consumption: The Effects of Education in the Household Compared to the Marketplace

Gary S. Becker and

Kevin M. Murphy

University of Chicago and Hoover Institution

This article considers various differences between the effects of education in the marketplace and households. It shows that the household sector rewards skills that are useful at the many tasks that household members must execute, whereas the marketplace rewards skill at specialized tasks. In addition, increased supplies of more educated persons reduce returns to education in the marketplace, whereas if anything, increased supplies raise household returns to education. The greater demand over 40 years for household and market skills may have raised returns to education in households compared to those in the market sector.

***

The Changing Role of Family Income and Ability in Determining Educational Achievement

Philippe Belley

University of Western Ontario

Lance Lochner

University of Western Ontario and National Bureau of Economic Research


We use the National Longitudinal Survey of Youth 1979 and 1997 cohorts to estimate the effects of ability and family income on educational attainment in the early 1980s and early 2000s. The effects of family income on college attendance increase substantially over this period. Cognitive ability strongly affects schooling outcomes in both periods. We develop an educational choice model that incorporates both borrowing constraints and a “consumption value” of schooling. The model cannot explain the rising effects of family income on college attendance in response to rising costs and returns to college without appealing to borrowing constraints.

***

The Production of Cognitive Achievement in Children: Home, School, and Racial Test Score Gaps

Petra E. Todd and

Kenneth I. Wolpin

University of Pennsylvania


This paper studies the determinants of children’s scores on tests of cognitive achievement in math and reading. Using rich longitudinal data on test scores, home environments, and schools, we implement alternative specifications for the cognitive achievement production function that allow achievement to depend on the entire history of lagged home and school inputs as well as on parents’ ability and unobserved endowments. We use cross‐validation methods to select among competing specifications and find support for a variant of a value‐added model of the production function augmented to include information on lagged inputs. Using this specification, we study the sources of test score gaps between black, white, and Hispanic children. The estimated model captures key patterns in the data, such as the widening of minority‐white test score gaps with age and differences in the gap pattern between Hispanics and blacks. We find that differences in mother’s “ability,” as measured by AFQT, account for about half of the test score gap. Home inputs also account for a significant proportion. Equalizing home inputs at the average levels of white children would close the black‐white and the Hispanic‐white test score gaps in math and reading by about 10–20 percent.

***

The Evolution of Income and Fertility Inequalities over the Course of Economic Development: A Human Capital Perspective

Isaac Ehrlich

State University of New York at Buffalo and National Bureau of Economic Research

Jinyoung Kim

Korea University

Using an endogenous‐growth, overlapping‐generations framework in which human capital is the engine of growth, we trace the dynamic evolution of income and fertility distributions and their interdependencies over three endogenous phases of economic development. In our model, heterogeneous families determine fertility and children’s human capital, and generations are linked via parental altruism and social interactions. We derive and test discriminating propositions concerning the dynamic behavior of inequalities in fertility, educational attainments, and three endogenous income inequality measures—family‐income inequality, income‐group inequality, and the Gini coefficient. In this context, we also reexamine the “Kuznets hypothesis” concerning the relation between income growth and inequality.

***

Enjoy!

best wishes,

Oskar

Sociobiology revisited: a new paper by Wilson and Wilson

An interesting review paper about multi-level selection was just made available (forthcomming) in the Quarterly Review of Biology by D S Wilson and E O Wilson. It's an interesting read. Here's the citation info and abstract:

RETHINKING THE THEORETICAL FOUNDATION OF SOCIOBIOLOGY

David Sloan Wilson

Departments of Biology and Anthropology, Binghamton University Binghamton, New York 13902 USA dwilson@binghamton.edu

Edward O. Wilson

Museum of Comparative Zoology, Harvard University Cambridge, Massachusetts 02138 USA

KEYWORDS

altruism, cooperation, eusociality, group selection, human evolution, inclusive fitness theory, kin selection, major transitions, multilevel selection, pluralism, sociobiology

ABSTRACT

Current sociobiology is in theoretical disarray, with a diversity of frameworks that are poorly related to each other. Part of the problem is a reluctance to revisit the pivotal events that took place during the 1960s, including the rejection of group selection and the development of alternative theoretical frameworks to explain the evolution of cooperative and altruistic behaviors. In this article, we take a “back to basics” approach, explaining what group selection is, why its rejection was regarded as so important, and how it has been revived based on a more careful formulation and subsequent research. Multilevel selection theory (including group selection) provides an elegant theoretical foundation for sociobiology in the future, once its turbulent past is appropriately understood.

The Quarterly Review of Biology, December 2007, vol. 82, no. 4

They are careful about defining their terms. Here are some useful definitions:

"sociobiology is the study of social behavior from a biological perspective, group selection is the evolution of traits based on the differential survival and reproduction of groups..."
"From an evolutionary perspective, a behavior can be regarded as social whenever it influences
the fitness of other individuals in addition to the actor."
"Group advantageous traits do increase the fitness of groups, relative to other groups, even if they are selectively neutral or disadvantageous within groups. Total evolutionary change in a
population can be regarded as a final vector made up of two component vectors, within and between-group selection, that often point in different directions."

They make a point that words like 'sociobiology' and 'evolutionary psychology' have become "tainted" due to their negative associations and bad reputations in many fields. This is of course especially true in the social sciences. I have almost never heard an anthropologist use sociobiology in a positive or even neutral context (only very negative - 'oh that stuff - we know better than that') but the vast majority of anthropologists would think of sociology as a field arguing that genes cause every observable trait we might observe - a much more extreme view than that used by its actual practitioners (above in the definitions).
In a similar vein, anything related to 'group selection' carries the connotation of being an automatically naieve argument even in fields where Darwinian analysis is accepted. I am mostly a behavioral ecologist (studying macroecological patterns) and I have been guilty of this. In many cases, arguments about group selection involve people speaking past each other and missing the point, this is why Wilson and Wilson often use the term 'multi-level selection' instead. We can show that altruism is costly to a perfectly self-interested actor but that a group of altruists out-competes a group of selfish social defectors. If we are comparing groups (populations) and focus only on individual-level benefits we may indeed miss part of the picture, but on the other hand the individual does a lot better in the group that doesn't get killed off by the more altruistic group. So the tension between the two views is not always necessary. Wilson and Wilson look at cases like the evolution of eukaryotic cells and argue that group selection must have been present to get the once autonomous entities (prob some form of early bacteria) to cooperate so closely in a tightly knit network of symbiotic mutualisms that they became organelles in the same cell.

So group selection must be common, they argue. Consider this view: "If a trait is locally disadvantageous wherever it occurs, then the only way for it to evolve in the total population is for it to be advantageous at a larger scale." Is altruism really locally disadvantageous though?

Getting back to relationships between groups, if we want to talk about why different populations spread at the expense of others then I think population level fitness measures are necessary and quite uncontroversially logical. George Williams himself proposed measures of population level fitness in his 1966 treatise against the brand of group selection proposed by Wynn-Edwards and others. [One of these measures was population density or size which he thought was not as good as the second measure, the numerical stability of the population through time, but this has much larger data requirements. These discussions are definitely relevant for our discussions of human evolution.] Wilson and Wilson also point out that there is room for multi-level selection in Williams' view, he only underestimated how frequently it could be important.

They are very careful to separate cogent arguments of multilevel selection from those they label naive group selection. The level of selection needs to be appropriate for the analysis being conducted. My feeling is that we can't categorically reject arguments of selection at the level of genes, individuals, families, other groups, maybe even species in some restricted geological cases like the study of mass extinction, and maybe higher levels like ecological network structures. Here's a nice quote they bring to this issue:
"In biological hierarchies that include more than two levels, the general rule is “adaptation at any level requires a process of natural selection at the same level and tends to be undermined by natural selection at lower levels.” All students of evolution need to learn this rule to avoid the errors of naı¨ve group selectionism. Notice that, so far, we are affirming key elements of the consensus that formed in the 1960s."

Humans are used as an example in many cases in the paper.
"The importance of genetic and cultural group selection in human evolution enables our groupish nature to be explained at face value. Of course, within-group selection has only been suppressed,
not entirely eliminated. Thus multilevel selection, not group selection alone, provides a comprehensive framework for understanding human sociality."

There seems little question that understanding how selection may play out at higher levels will be necessary for explaining how anatomically modern humans came to spread and conquer the globe. But we do need to be cautious with how such arguments are invoked.

This paper is extremely well written and thought provoking. I recommend checking it out.
Best,
Oskar

Complex Systems Summer School 2008

The Santa Fe Institute is now looking for applications for next year's complex systems summer school. I attended the international school in Beijing 2005 and loved it (went back the next year as staff). I recommend it for folks interested in complex systems research from any perspective.

Here's the basic information on the school and how to apply (this is just the text of the email they send to alumni to help circulate the announcement):

_____

Complex Systems Summer Schools

Summer 2008

The annual Complex Systems Summer Schools provide an intensive introduction to complex behavior in mathematical, physical, living, and social systems for graduate students and postdoctoral fellows. Schools will be held in Santa Fe, New Mexico and Beijing, China. Applications are now available at http://www.santafe.edu/csss08.html.

Program Details

Santa Fe: June 1-28, 2008 at St John’s College in Santa Fe, New Mexico, USA. Directed by Dan Rockmore, Dartmouth College and Santa Fe Institute (SFI); administered by the Santa Fe Institute (SFI).

Beijing: June 30-July 25, 2008. Sponsored by SFI in cooperation with The Institute of Theoretical Physics, the Chinese Academy of Sciences (CAS). Co-directors: Dr. David P. Feldman, College of the Atlantic and SFI, and Dr. Chen Xiao-song, Institute for Theoretical Physics, CAS.

General Description

The Complex Systems Summer School offers an intensive four-week introduction to complex behavior in mathematical, physical, living, and social systems for graduate students and postdoctoral fellows in the sciences and social sciences. The schools are for participants who want background and hands-on experience to help prepare them to do interdisciplinary research in areas related to complex systems.

Each school consists of an intensive series of lectures, laboratories, and discussion sessions focusing on foundational ideas, tools, and current topics in complex systems research. These include nonlinear dynamics and pattern formation, scaling theory, information theory and computation theory, adaptation and evolution, network structure and dynamics, adaptive computation techniques, computer modeling tools, and specific applications of these core topics to various disciplines. In addition, participants will formulate and carry out team projects related to topics covered in the school.

Further details about topics and faculty at each school will be posted

as they become available.

Eligibility

Applications are welcome from all countries. Participants are expected to attend one school for the full four weeks. All activities will be conducted in English at both schools. No tuition is charged, and some support for housing and travel expenses is available. Enrollment is limited.

Applications are solicited from graduate students and postdoctoral fellows in any discipline. Some background in science and mathematics (including multi-variate calculus and linear algebra) is required. Proficiency in English is also required.

Students should indicate school location preference when applying. Placements may be influenced by restrictions in U.S. foreign visitor policies.

Application Requirements

1. Current resume or CV. Include a clear description of your current educational or professional status, and a list of publications, if any.

2. A statement of your current research interests and comments about why you want to attend the school (suggested length: one to two pages).

3. Two letters of recommendation from scholars who know your work.

How to Apply

Online: Our online application form allows you to submit all of your materials electronically (including a feature which allows your recommenders to upload letters of recommendation directly to your file). We strongly encourage you to apply online to expedite your application.

Postal Mail/Courier: Applications sent via postal mail will also be accepted. Include a cover letter providing your e-mail address and fax number, and specifying whether you wish to be considered for a travel scholarship. (This will not influence the review of your application.) Do not bind your application materials in any manner. Send application materials to:

Summer Schools

Santa Fe Institute

1399 Hyde Park Road

Santa Fe, NM 87501 USA

If applying via post, letters of recommendation may be sent separately to the address above, or included in your application package in sealed envelopes.

DEADLINE

All application materials, including letters of recommendation, must be received at SFI or electronically submitted no later than January 7, 2008.

Women, minorities, and students from developing countries are especially encouraged to apply.

If you have further questions about the Complex Systems Summer Schools, please e-mail goodwin@santafe.edu

Human Macroecology on Facebook

I've created the "Human Macroecology" group on Facebook to help us keep in contact. Join if you dare.

Island Rule Paper

Ok, I am admittedly way behind on this, as the paper I'm now blogging about came out over a week ago but given that we've posted about the Island Rule in here before, I'd feel remiss if we didn't cover a paper arguing that this well known rule from biogeography is a statistical artifact. If you are wondering why human ecologists should care about the Island Rule, that is also addressed in the previous post. So, this paper was published in the Proceedings of the Royal Society:

title: The island rule: made to be broken?

authors: Shai Meiri, Natalie Cooper, and Andy Purvis

abstract: The island rule is a hypothesis whereby small mammals evolve larger size on islands while large insular mammals dwarf. The rule is believed to emanate from small mammals growing larger to control more resources and enhance metabolic efficiency, while large mammals evolve smaller size to reduce resource requirements and increase reproductive output. We show that there is no evidence for the existence of the island rule when phylogenetic comparative methods are applied to a large, high-quality dataset. Rather, there are just a few clade-specific patterns: carnivores; heteromyid rodents; and artiodactyls typically evolve smaller size on islands whereas murid rodents usually grow larger. The island rule is probably an artefact of comparing distantly related groups showing clade-specific responses to insularity. Instead of a
rule, size evolution on islands is likely to be governed by the biotic and abiotic characteristics of different islands, the biology of the species in question and contingency.


So the issue in this and lots of studies that look at body size related trends is whether or not species can be treated as independent data points or whether adjustments have to be made for the phylogenetic relatedness of the species. That is, a bunch of species could exhibit a similar trend in something simply because they are closely related and if this is not adjusted for then we run the risk of identifying trends that we think are related to body size but are really just due to genetics/ancestry. Let's pretend that there are 3 camps on this issue - those that think you always have to adjust for phylogeny, those that think you have to sometimes, and those that think you never do. The authors of this paper would be in the first group, I would be in the second. Issues of statistical independence may indeed be under-appreicated in cross-species analysis of the sort common in biogeography and in studies of allometry. But as Jim Brown has pointed out (in informal lab-meeting type settings) it is not always clear exactly what things need to be controlled for in any given analysis. So, sure, for some things phylogeny might be the most important but in others it could be something like biome or some attribute of the niche that is occupied - or some general feature of ecology. There could potentially be a lot of uncontrolled confounds out there... How do we know which ones are most important, especially when we rarely have data on all of the potential variables we might want to examine?

So, this paper specifically argues that the trends that we think are behind the Island Rule are due to lineage specific responses to island colonization. That due to some issue of shared ancestry different but related species consistently respond similarly to island environments with respect to body mass change simply because they are related and not because of any general relationship between the mass of a colonizing organism and the island environment. The authors point out that none of the papers that have previously looked at the Island Rule have considered the role of phylogeny. After using methods that control for phylogeny, they state that:
"We did not find convincing evidence that larger size leads to insular size reduction within mammals in general (using independent contrasts) or within clades. Neither do we find that, as a rule, large mammals dwarf on islands nor that small mammals grow large..."

I'll also include a quote from their methods:
"We used only those studies that reported body size of mainland populations geographically closest to the island in question (Lawlor 1982). Some insular populations have their nearest
sister taxon on a mainland areawhich is a considerable distance away (e.g. Hafner et al. 2001). The paucity of good intraspecific phylogenetic data, however, precludes us from identifying the
closest relatives for most insular populations and we therefore use geographical distance to approximate phylogenetic affinity."

The issue of when we can and when we can't use species as data points won't be fully resolved any time soon. I'm sure that this paper will lead to some careful attention to this issue in the biogeographic community.

Cheers,
O

Next year's human ecology conference

The call for participation in next year's human ecology conference has just recently been announced. The theme for this meeting seems quite relevant for a lot of the things we've discussed this semester (and is also on something we didn't spend much time on) and I encourage interested parties to think about attending or even presenting. The conference proposes to focus on "Integrative thinking for complex futures: creating resilience in human-nature systems." The conference is the official meeting of the Society for Human Ecology. Information about the call for papers and the theme of the conference are posted in .pdf format.
cheers,
O

New scaling paper: Organisms as 4 dimensional objects

A new paper has just been released as forthcoming in American Naturalist that takes a novel and curious approach to scaling in ecology and evolution. I'll elaborate on the paper below but first a bit of context:

We've talked some about scaling relationships and why they emerge but haven't gotten too much into the details of the theories attempting to explain why certain scaling properties exist. These fall into two camps, life history models that usually take certain extrinsic properties as givens and more complicated physical models that attempt to explain why metabolic rate is body mass to the 3/4 power from first principles of energetics and geometry. Examples of life history models predicting the allometries for traits like birth rate, mortality rate, age at first reproduction, and life span are those of Charnov (1991, 1993, 2001). These tend to take factors like the production function (growth rate is some constant a*mass^(3/4)) as a given and predict the other allometries, which tend to be +1/4 powers for times (life span, generation length, etc) or -1/4 powers for rates (birth rate, mortality rate, intrinsic rate of increase r, etc.). These models often have mortality rate as an external environmental parameter, but not always, and often take size at independence as a given (which is a linear function of adult mass and this predicts the -1/4 power scaling of fertility rate). One very successful geometric model is presented in West et al. (1997, 1999) and demonstrates that the 3/4 scaling of metabolic rate results from an optimal solution to the problem of efficiently constructing biological resource distribution networks that must deliver resources to all the cells in an organism while satisfying certain design characteristics. That is, the network should efficiently fill space and deliver resources to cells as effectively as possible. This problem generates a fractal distribution network that optimally fills space and generates a predicted 3/4 power of metabolic rate with mass. The 'networks' we are referring to in this context are vascular systems in plants and circulatory systems in animals. (This treatment is shockingly rudimentary but hopefully good enough for present purposes).


This paper by Lev Ginzburg and John Damuth takes a different view on scaling relationships in ecology by looking at the dimensionality of organisms. First, here's the citation info and abstract. I'll continue to comnent below.

The Space‐Lifetime Hypothesis: Viewing Organisms in Four Dimensions, Literally

Lev Ginzburg^1, and

John Damuth^2,

1. Department of Ecology and Evolution, Stony Brook University, Stony Brook, New York 11794;

2. Department of Ecology, Evolution and Marine Biology, University of California, Santa Barbara, California 93106

Abstract:

Much of the debate about alternative scaling exponents may result from unawareness of the dimensionality appropriate for different data and questions; in some cases, analysis has to include a fourth temporal dimension, and in others, it does not. Proportional scaling simultaneously applied to an organism and its generation time, treating the latter as a natural fourth dimension, produces a simple explanation for the 3/4 power in large‐scale interspecies comparisons. Analysis of data sets of reduced dimensionality (e.g., data sets constructed such that one or more of the four dimensions are fixed), results in predictably lower metabolic exponents of 2/3 and 1/2 under one and two constraints, respectively. Our space‐lifetime view offers a predictive framework that may be useful in developing a more complete mechanistic theory of metabolic scaling.

The authors argue that organisms can literally be viewed as four dimensional objects, three spatial and one temporal. While many traits scale with body size, they specifically focus on the well-known finding that metabolic rate scales as the +3/4 power of body mass whereas lifespan goes as the +1/4 power. This makes the product of the two an isometric relationship (m^3/4 x m^1/4 = m¹), such that a doubling in an organism’s size predicts a doubling in the energy it metabolizes in a lifetime. While many researchers take this as a consequence of other scaling relationships, it plays a fundamental role in the 4D view. As they state it, “these observations suggest instead that the scaling of lifetimes may reflect a fundamental manner in which organisms of all body masses are ecologically and evolutionarily functionally similar.” Thus the organism’s four dimensions, three spatial (length, area, volume) and one temporal (generation time) together give m¹. If these four dimensions are evenly divided into the isometric scaling of lifetime metabolic rate then each will be m^1/4. This predicts that metabolic rate should be m^3/4 because energy is taken in through a 3D surface and then allocated to processes that take place in 4D (the dimension of time and within the 3 dimensional space of the organism). And if metabolic rate is m^3/4, the remaining dimension, generation time (or lifespan), should be m^1/4 to preserve the isometric scaling lifetime metabolic rate.

The role of generation time in ecology and evolution itself is another key component of the 4D argument: “Constructing one viable and reproductively capable daughter requires a certain duration (a “generation time”) that is conveniently viewed as an organism’s fourth dimension. So, on average, it takes a generation time of metabolism for a mother to guarantee the existence of her replacement.” This establishes the reasoning for why generation time is fundamentally an organism’s fourth dimension.

Where this argument becomes even less conventional is in the stated lack of a mechanism. In fact, my reading of the paper is that they intend the argument to predict the set of criteria to which any proposed mechanistic explanation of ¾ power scaling in biology must conform. For instance, they can predict that progressive reductions in dimensionality, by holding constant generation time, length, etc. should lead to predictable reductions in the exponent. So if generation time is held constant then they predict that metabolic rate should be a 2/3 power of mass, rather than ¾, and cite examples where within species metabolic rates have been shown to go as the 2/3 power of mass (if length and generation time are held constant, as with species of same size and lifetime, the scaling should be ½, etc.). They do this with multiple regressions. For instance, they predict that if height and generation length are controlled for, then metabolic rate should scale as the 1/2 power of mass and their data seem to conform to this prediction.

Because they do not suggest a mechanism, they are not necessarily at odds with any particular theory of metabolic scaling, such as that of the space-filling fractal geometry of supply networks in the circulatory and vascular systems of mammals and plants (e.g., West et al. 1999 - mentioned above). The explicitly non-mechanistic argument in the paper adds to its uniqueness but is also where some people may have the greatest trouble with the paper, as we are taught to focus on mechanisms and this nature of dimensional thinking is much more foreign to us (and maybe difficult to interpret at first). The theory makes simple and elegant predictions that should lead readily to either coherence or conflict with some of the existing takes on the topic (note that I'm saying the predictions are simple and elegant but am not saying anything about whether the empirical results are broadly accurate. Its of course too soon to see if how these predictions will weather the tests of time. They do give some good empirical support in the paper). Either way, dimensional thinking is a novel approach in this area that, when combined with the argument for the importance of generation time, makes a fundamental contribution to the literature and will certainly alter future approaches to the subject of scaling in ecology.

Well, something to think about anyway.

Oskar

New paper "Global climate change, war, and population decline in recent human history"

(Published before print by Zhang et al. in PNAS, vol. 104, no. 49)

A successful example of macroscopic and interdisciplinary approaches to human ecology. Their abstract provides a nice appetizer:

"Although scientists have warned of possible social perils resulting
from climate change, the impacts of long-term climate change on
social unrest and population collapse have not been quantitatively
investigated. In this study, high-resolution paleo-climatic data
have been used to explore at a macroscale the effects of climate
change on the outbreak of war and population decline in the
preindustrial era. We show that long-term fluctuations of war
frequency and population changes followed the cycles of temperature
change. Further analyses show that cooling impeded agricultural
production, which brought about a series of serious social
problems, including price inflation, then successively war outbreak,
famine, and population decline successively. The findings
suggest that worldwide and synchronistic war–peace, population,
and price cycles in recent centuries have been driven mainly by
long-term climate change. The findings also imply that social
mechanisms that might mitigate the impact of climate change were
not significantly effective during the study period. Climate change
may thus have played a more important role and imposed a wider
ranging effect on human civilization than has so far been suggested.
Findings of this research may lend an additional dimension
to the classic concepts of Malthusianism and Darwinism."

Enjoy!
Jordan

Toward a human macroecology

“Students will view human ecology from the complementary perspectives of biogeography and macroecology, showing patterns across space and time, and system dynamics, focusing on ways energy, materials, and information are processed and transformed in social systems.” From the Perspectives in Human Ecology course syllabus

In fact, we have looked at human ecology through several lenses: life history, biogeography, and systems theory. A glance through a photography magazine shows the power of different perspectives, often achieved using different lenses: magnifying, light-filtering, UV illuminating, and so on. Are the perspectives through which we’ve viewed human ecology truly complementary? Can we layer them to produce a distinct, penetrating vision of the human condition?

More specficially, do such seemingly disconnected patterns as the decrease in stature with population density (R. Walker), the latitudinal cultural diversity gradient (Collard & Foley), the organization of Balinese water temple networks (Lansing & Kremer), the demographic transition (Moses & Brown), and the scaling relations of cities (Bettencourt et al.) share a common currency? If so, what is the underlying economy of human nature?

In what ways is human macroecology, to name our overarching approach, a productive perspective, as Turchin would say? Does it clarify and reveal patterns and connections that other perspectives do not? What is its scope? What are its strengths and weaknesses? How might we improve it or alter it? And what are its evolving frontiers?

Finally, given Ginzberg’s caveats about natural laws—that we should not expect them to be exceptionless, inevitably predictive, and even explanatory or discerning of cause and effect—are there candidate “laws of human ecology?”

Contribute your thoughts to the blog, and come prepared to discuss them in class tomorrow.

Looking forward to our synthesis….

Bill

UNM Statistics Clinic

This may be helpful to some of you doing empirical work for your papers. I just found out that Math&Stat department offers a statistics clinic that's free to UNM students, staff, and faculty.

Week 15: Human Macroecology and Historical Dynamics/Course Wrap-up

Greetings All,
This week we are reading a chapter from Peter Turchin's book, War and Peace and War: The Rise and Fall of Empires (2006). The chapter, War and Peace and Particles, outlines Turchin's approach to the study of human history. We are not reading this to understand history or how it should be studied, although we will likely discuss this some, but rather to notice any similarities between human macroecology and the perspective on history that Turchin is trying to build and define. Turchin's arguments relate to some of the things we've discussed about laws and emergent phenomena and his approach to the relationship between individual actions and macroscopic patterns provides an excellent frame for some of our past discussions.
The Chapter we are reading is the beginning of part 3 of the book, which has the goal of defining this scientific approach to the study of history that he calls "cliodynamics." The book is written for a general audience and is generally very well written and easy to follow. However, two terms are mentioned briefly in this chapter, metaethnic frontier and asabiya, that are central to Turchin's theory of historical dynamics. I am elaborating on the definition of these terms and including two excerpts from earlier chapters of his book for the sake of clarity and context on how he uses them

Metaethnic frontiers are defined on pages 5 - 6 (of Turchin 2006) and this leads directly to the role of asabiya in historical dynamics.
The concept of metaethnic frontier emphasizes the importance of ethnicity as a marker of boundaries between groups, be they based on language, rituals, or symbols of dress and custom. Ethnicities are usually nested within each other and single empires may dominate multiple ethnicities, which then may or may not come to share a feeling of solidarity for the empire. Turchin further explains his use of the term as follows:
"The broadest groupings of people that unite many nations are usually called civilizations, but I prefer to call such entities metaethnic communities (from the Greek meta, 'beyond,' and ethnos, 'ethnic group' or 'nation'). My definition includes not only the usual civilizations - the Ester, Islamic, and Sinic, - but also such broad cultural groupings as the Celts and Turco-Mongolian steppe nomads. Typically, cultural difference is greatest between people belonging to different metaethnic communities; sometimes this gap is so extreme that people deny the very humanity of those who are on the other side of the metaethnic fault line.
Historical dynamics can be understood as a result of competition and conflict between groups, some of which dominate others. Domination, however, is made possible only because groups are integrated at the micro level by cooperation among their members. Within-group cooperation is the basis of inter-group conflict, including its extreme versions such as war and even genocide.
Different groups have different degrees of cooperation among their members, and therefore different degrees of cohesiveness and solidarity. Following the fourteenth-century Arab thinker Ibn Khaldun, I call this property of groups asabiya. Asabiya refers to the capacity of a social group for concerted collective action. Asabiya is a dynamic quantity; it can increase or decrease with time. Like many theoretical constructs, such as force in Newtonian physics, the capacity for collective action cannot be observed directly, but it can be measured from observable consequences."

[A metaethnic frontier is a frontier or border between different metaethnic communities.]

The concept of asabiya is "the capacity for social action." The propensity for a group to have asabiya is key to understanding the results of conflicts between empires. It is a central topic in this book and Turchin's earlier monograph on the topic of historical dynamics (Historical dynamics: why states rise and fall). Turchin finds the human potential to cooperate as a crucial social capacity, as it leads to a willingness to make huge sacrifices for the good of some broader social unit.
Asabiya as a concept is thoroughly defined on page 91 as follows:
"The concept of collective solidarity, or asabiya in Arabic, was Ibn Khaldun's most important contribution to our understanding of human history. The theory is described in his monumental The Muqaddimah: An Introduction to History. Asabiya of a group is the ability of its members to stick together, to cooperate: it allows a group to protect itself against the enemies, and to impose will on others. A group with high asabiya will generally win when pitched against a group of lesser asabiya. Moreover, 'royal authority and general dynastic power are attained only through a group and asabiya. This is because aggressive and defensive strength is obtained only through... mutual affection and willingness to fight and die for each other.' In other words, a state can be organized only around a core group with high asabiya. By acting in a solidary fashion, the members of the core group impose their collective will on other constituents of the state and thus prevent the state from falling apart.
But it is not enough to identify group solidarity as the main factor responsible for the strength of the state. Why do some groups have it in abundance, whereas others do not?"

So there's some background on Turchin's goals and use of these terms. We of course are focusing more on the nature of his perspective than specific understandings of history but both are certainly open for discussion.

Like last week there is no annotation for this week but please post a couple of questions and/or comments about War and Peace and Particles on this blog.

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Some course-related details to keep in mind:
The next two class periods are the wrap-up for the content of the course. On Tuesday (11/27/07) we discuss Turchin and use it as a springboard for Thursday (11/29/07) when we define human macroecology, its goals, techniques, future prospects and limitations. On Thursday we will outline a blog entry and wikipedia article on human macroecology.
As a reminder, please also revisit the readings from the very first week. It may be the case that your take on this first assignment has changed a good deal and it will also be useful for discussion.

Next, we have student presentations. These are the last two class periods of the semester (12/04/07 and 12/06/07). These are informal presentations that have to be less than ten minutes each. Each presenter can get a max of 4 slides which must be emailed to us before hand. We'll have the slides ready for the order of the speakers. The order will be determined with a sign-up sheet on Tuesday of this week.

The presentations are of course about the content of your final papers. These are due on the Wednesday of finals week at 12:00 noon (that's 12/12/07 at 12!).

Another item is the final conversation or oral dialog. This is effectively a final exam where we will ask about your impressions of topics during the course as well as test your comprehension of the major themes of the semester and the arguments of the papers. These will be on the Monday, Tuesday, and Wednesday of finals week and we'll figure out specific exam times with a sign-up sheet in class.

As always, please let us know if you have any questions.

Cheers,
Oskar

Gapminder video

Hey everyone,
Great discussion today. As always there was a lot more we could have talked about, both in terms of the scientific perspectives involved and the implications of the arguments in the papers. As the semester wraps up, spend some time thinking about what this class is all about and how you might apply what we've learned to your own interests. What were the main points, implications? We ended up going over sustainability some and how to manage human economies. But lets not forget about the macroscopic viewpoint and the mechanistic approach to understanding underlying rules that govern some of the complexity of human systems. Keep in mind that claims of absolute human uniqueness are abundant in many fields of study, yet in many cases human systems seem to exhibit behaviors that are extensions of other natural systems (but not always). Some of you will focus more on the applied aspects of the work we've covered and some on the macroecology of scaling, complexity, and life history we've gone over. Hopefully these themes come together and we are all simultaneously more responsible broad thinking scientists and students-at-large.
But this is all a digression that leads to the video below. I realize that many of you may not have spent a lot of time on the links I posted the other day. I really recommend visiting the gapminder site. Its informative and plays on a lot of themes that we've covered. I'm posting one particular speech by Hans Rosling but I could have chosen any of a number on his website. This one is particularly entertaining and information filled - and has some messages toward the applied end of big picture thinking. This speech is a bit long so set aside a few minutes (and I wouldn't try to watch it on a slow connection). Also note that all of the graphical stuff he does at the beginning of the talk is part of the interactive software on the website so you can all play with it.
Have a good break,
O

Week 14: Economics of energy in human systems

Hey everyone,
Please read the following paper for next week:

Hall et al. 2001. The need to reintegrate the natural sciences with economics. Bioscience 51: 663-673.

(recommended) Smil, V. 2000. Energy in the twentieth century: Resources, conversions, costs, uses, and consequences. Annual Review of Energy & Environment 25: 21-51. (at least look at graphs and highlighted sections, for which will need latest version of Adobe reader)



Figures: Electricity use for night-time
lighting at global, national, and
local (Albuquerque) scales
(click on figures for larger view)


Note: No annotations due this week (Thanksgiving week), but please post your blog comments.




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Like organisms, human societies run on energy, and their energy use and characteristics scale with their size. At a minimum, societies need enough energy to fuel the bodily metabolisms of its members. As traditional foragers aggregate into larger groups, they require proportionately less land, suggesting that larger societies, like larger animals, metabolize energy more efficiently (Hamilton et al., 2007b). As people aggregate further, forming large urban settlements, their per-capita infrastructure costs continue to fall with population size, while their gross productivity and creative output rise (Bettencourt et al., 2007). As the average energy use of people along this spectrum increases, they tend to invest more energy in fewer offspring (Moses & Brown, 2003). In essence, a metabolic view of societies illuminates modern changes in human life-history tradeoffs at an individual level and, arguably, at a societal level.

This week, we will examine the role of energetic resources in fueling social metabolism and growth and on accounting for the central role of energy in human economies. It’s not required, but read the highlighted portions and graphs of Smil, 2000, if you have time. Smil, presents an eye-opening history of modern fuel use that shows the central role of external energy in fueling modern human society and social transformations & transitions. How might Smil’s account relate to Tainter’s ideas about high and low gain systems, Hollings ideas on adaptive cycles, and a general “systems” perspective on human ecology?

In arguing for integrating nature’s constraints into mainstream economics, Hall et al., 2001, provides a springboard for embedding hierarchical socio-economic systems within broader biophysical systems. Fig 2 presents a good view of this idea. We chose Hall not to launch a polemic against standard economics but rather to stimulate discussion on widening our systems perspective to include nature’s economy, especially the role of energy. From a geographic perspective, how do energy sources “map on” to the distribution of humans on the globe? Is a Diamondesque view helpful, that the geography of energy sources influences patterns of wealth and development? How are these sources distributed, both originally and through redistribution networks, and what are the implications?

Hall et al., 2001, also raise the issue of integrating ecology and economics, which have natural parallels and paradigms. Both ecology and economics come from the Greek “oikos,” meaning “house.” They share similar ideas of “capital” as wealth, monetary wealth in economics and the “embodied capital” of the body and its abilities in human evolutionary ecology. Ecology’s food webs are clearly akin to human economies of buyers, sellers, firms, and so on. And optimization plays key roles in life history theory (i.e. fitness maximization) and economic theory (i.e. utility maximization). A well-known ecology textbook encapsulates the ideas that natural systems run on energy and use it efficiently in its title, The Economy of Nature. As Brown et al. discuss in “The fractal nature of nature,” a scaling perspective of human ecology makes the same argument.

Given how wide-ranging the idea of valuing natural resources generally*, I’d rather focus on energy and build explicitly on our conceptual foundations in systems theory, scaling, and life history. Economists Herman Daly, Partha Dasgupta, Robert Constanza, and Kenneth Arrow, among others, have written extensively on the importance of proper valuation of natural resources and the related concept of sustainability. From ecology, H.T. Odum pioneered an energetic perspective, and C.S. Holling, Carl Folke, Lance Gunderson, and Stephen Carpenter have further developed “systems ecology” with humans and energy in mind.

We’re considering the value of a systems perspective of human ecology. How does it differ from traditional views? This macroscopic view uses scaling and hierarchy theory to backlight the often invisible networks that move and connect genes, energy, and information. It uses complexity theory to understand how nodes in these networks, such as actors on an agricultural landscape, use simple rules to generate emergent, systemic behavior. And it effectively uses economic theory to see how costs, benefits, and trade-offs connect individual decisions to global outcomes.

Looking forward to our discussion,

Bill

* See Daily et al. 2000. The value of nature and the nature of value. Science 289: 395-396 for a good general discussion of valuing ecosystem services written by a “who’s who” of ecologists and economists.

** If you're curious, here's a link to the New Mexico state profile from the U.S. Energy Information Administration, which has a wealth of information: http://tonto.eia.doe.gov/state/state_energy_profiles.cfm?sid=NM

New web-related resources

What's up everybody.
I've been meaning to add a few new blogs and links to the sidebar for some time and I'm just doing this now to point them out.
A couple of folks told me about this New York Times page on environmental issues. Its worth checking out.
Also from New York Times - next time you want to accidentally spend a few hours of your life in cyberspace, the Freakonomics blog is addictive, entertaining, and you can even learn stuff.
Another really good (and popular) link that I've been meaning to put up for a while, right here on blogspot, is the Dieneke's Anthropology Blog.
And last but not least, our very own British human macroecologist living in Mexico, has just updated his personal website with info about his research and whatehaveyou. Check out Marcus Hamilton's new site here.

I hope you take advantage of these and the other links on this site as they are fun and efficient ways to get good information, or at least some fairly intellectual entertainment.

Best wishes,
O

PS! And this just came to my attention. This is one of the coolest web resources I've ever seen. Maybe the coolest for anyone with an interest in big picture patterns of human demography. I highly recommend you all spend some time at gapminder.org.

Hello human ecologists. I must say, I’ve been watching this blog from afar (well, from Mexico) with a fair amount of awe at the range of material you’ve been covering. I wish I’d had a class like this! For that matter I wish all anthropologists and ecologists had a class like this.

So, here’s a bit of background for the Hamilton et al. 2007 Proc Roy Soc Lond Ser, B paper you’re reading as one of the papers this week. This paper, and its companion, Hamilton et al. 2007 PNAS 104, arose from spending a lot of time with Oskar, going to the Biocomplexity Seminar a few years ago (now defunct) and hearing week after week about metabolic scaling theory and complex biological systems. After several months of trying to get my head around what it all meant, it suddenly occurred to me that if all these simple scaling laws lead to all this emergent complexity (and simplicity) in ecological systems, due to the fundamental constraints of physics, chemistry, thermodynamics etc, then the same must be true for human systems as we too are simply another biological species making a living within complex ecosystems. That is to say, as ecosystems are structured by the flows of energy, matter, and information between organisms and their environments, and these flows lead to scaling laws and complex structures, then human systems should display the same kinds of attributes. This should be true especially for those human systems that are arguably most subject to ecological heterogeneity, hunter-gatherers.

A couple of years prior, Louis Binford (2001) had published a large volume of research on hunter-gatherers, mainly from an archaeological perspective. But in that book he included tons of data on a worldwide sample of hunter-gatherer societies (n = 339) he had compiled, including simple metrics such as population size, territory size, and group size estimates at various levels of organization, as well as all kinds of ecological and environmental variables. So I asked the question, are hunter-gatherer societies complex adaptive systems? That is, is there something about their structure at one level, some emergent property, that arises from some underlying principle that feeds-back to impact individual fitness? So the first thing I noticed was what ended up in the Royal Society paper: There is a striking geometric scaling of group size (or strictly speaking, group size frequencies) across all levels of organization, and this is a classic pattern found in all kinds of complex systems (i.e., a hierarchical, modular, self-similar branching structure). This pattern denotes statistical self-similarity, and these fractal structures are found throughout nature from metabolic networks to the structure of river basins.

The second question was then, what kind of effect could this structure have on some measure of population efficiency? But more importantly, how might I measure this? This was answered by plotting population size as a function of territory size recognizing that the area a population uses is roughly equivalent to its energy catchment area. Because the scaling relation we found was sublinear, this means that population size increases faster than energy use (territory size), so larger populations are more energetically efficient than smaller ones. Moreover, the scaling relation we found, ~3/4, was suspiciously similar to the scaling of metabolic processes found throughout living systems. Therefore, hunter-gatherer social systems seem to show signs of a “social metabolism”, for what seemed to be the same reason as other biological systems, namely a fractal-like branching distribution network.

So this sublinear scaling (~0.75) demonstrates an economy of scale in hunter-gatherer socio-economies. Note that in the Bettencourt et al. paper (very cool paper), they find similar scalings for economies of scale in urban systems, ~0.8, yet they don’t suggest a mechanism. Might we have a universal scaling law for human economies of scale, from hunter-gatherers to urban economies? Watch this space...

Marcus

Week 13: Scaling part 2

The following papers are required readings for next week. A few optional papers are in the ereserves folder as well.

*Hamilton M. et al. 2007. The complex structure of hunter-gatherer social networks. Proceedings of the Royal Society of London, Series B.

* Bettencourt, L. M. A., J. Lobo, D. Helbing, C. Kuhnert, and G. B. West. 2007. Growth, innovation, scaling, and the pace of life in cities. Proceedings of the National Academy of Sciences 104:7301.

*Moses, M. E., and J. H. Brown. 2003. Allometry of human fertility and energy use. Ecology Letters 6:295-300.

"Nets versus Nature": an interesting News and Views

David Conover writes an interesting News and Views piece in the current Nature about a paper published this week in PNAS (here). Here's what he has to say about it:

"People like to catch big fish, sometimes so much so that fish sizes overall become greatly diminished. According to one view, the continual removal of large fish from a population sets the stage for rapid, undesirable evolutionary changes, including slower growth, earlier adult maturation and permanently smaller size^{1, 2}. This occurs because removing the largest fish directly opposes natural selection, which tends to favour large size.

What happens when these two forces simultaneously oppose one another? Can evolution respond quickly enough to track changes in fishing selection, or does natural selection counteract it? Writing in Proceedings of the National Academy of Sciences³, Eric Edeline and colleagues illustrate the outcome of this dynamic tug-of-war between the forces of natural selection and fishing selection."

He points out that the role of natural selection is often not considered in fishery's management because of the assumption that humans are just another predator in the system and we just need to regulate how much that one predator harvests. However, this paper shows that the size selective nature of human predation can have really different effects than other sources of mortality (including nonhuman predators), which tend to impact smaller, slower, weaker individuals. Thus, typical predators create selection for large size because not only is fitness generally higher at large mass but fewer things will eat you - whereas humans create pressure against it. The authors of the PNAS paper demonstrate these opposing forces empirically with a unique and high resolution data set on Pike in Lake Windermere, England. Humans did indeed selectively take large individuals whereas other sources of mortality weeded out the small. They also showed the predicted life history relationships between fishing intensity and growth rate, which are consistent with the models we discussed earlier in the semester.

This paper isn't written from the perspective of human ecology (although I'm sure lots of human ecologists are very interested in this) but it fits the aims of this class very well because it uses life history theory to demonstrate a relatively simple but previously somewhat overlooked feedback that underlies human predation and and a key ecological pattern. ...er something like that anyway...

Introduction to Week 12 and 13: Scaling in human ecology

Metabolism, life-history, innovation, self-similarity, and social organization

The study of complex systems necessitates understanding the fundamental role of scale and hierarchical levels in governing dynamics and pattern formation. Scaling is a powerful tool used to relate the attributes of a system to changes in dimension. The next two weeks’ readings provide a brief introduction to issues of scale and a more in depth exposition of the recent uses of the scaling approach in human ecology.

Building on allometric and metabolic scaling, the recent metabolic theory of ecology is experiencing great success and controversy because it potentially provides a unifying framework for understanding the flows of energy and materials in ecological systems, as discussed by Brown et al. (2004). How might this theory and approach be extended and adapted to apply to human systems? Moses and Brown find that fertility rate in humans scales with metabolic rate just like in other organisms when total extra-metabolic energy consumption (e.g., electricity and gasoline use) is used as measure of metabolic rate, instead of physiological metabolic rate (Fig.1). But could this similarity be purely coincidental? A rigorous theory is necessary to demonstrate otherwise.

Bettencourt et al. (2007) discuss how cities are similar to and different from biological organisms. They suggest that their social organization, the cooperative interaction between individuals, leads to scaling relations uncommon in organisms, such as the scaling of wealth creation and innovation with city size. Yet how different are scaling relations for cities different from those in sedentary groups of other highly social organisms, such as ant colonies? In any case, an important step in the development of a metabolic theory of ecology will be to include the effects of interactions between agents, whether between individuals in a social group, species in a food web, or nations in a global environment.

Fractals and self-similarity pervade throughout the natural world. They emerge when a process is repeated across a range of a dimension. Due to the simplicity of the processes necessary for their origin and their commonness in nature, in many cases it may even be most appropriate to consider them as null models (e.g., in the spatial distribution of resources). Hamilton et al. (2007) discover an apparent self-similarity in the structure of social networks in hunter-gatherers. They suggest an intimate link between social organization and metabolism in hunter-gatherers (see also Hamilton et al. , 2007, PNAS).

As Brown et al. (2002) write, “Underlying the diversity of life and the complexity of ecology is order that reflects the operation of fundamental physical and biological processes”. Through the use of scaling, these readings investigate the potential existence of such order in human systems.

References

* Bettencourt, L. M. A., J. Lobo, D. Helbing, C. Kuhnert, and G. B. West. 2007. Growth,
innovation, scaling, and the pace of life in cities. Proceedings of the National Academy of Sciences 104:7301.

*Brown, J. H. 2002. The fractal nature of nature: power laws, ecological complexity and biodiversity. Philosophical Transactions: Biological Sciences 357:619-626.

*Brown, J. H., J. F. Gillooly, A. P. Allen, V. M. Savage, and G. B. West. 2004. Toward a Metabolic Theory of Ecology. Ecology 85:1771-1789.

*Gibson, C. C., E. Ostrom, and T. K. Ahn. 2000. The concept of scale and the human dimensions of global change: a survey. Ecological Economics 32:217-239.

*Hamilton M. et al. 2007. The complex structure of hunter-gatherer social networks. Proceedings of the Royal Society of London, Series B.
*Hamilton, M. J., B. T. Milne, R. S. Walker, and J. H. Brown. 2007. Nonlinear scaling of space use in human hunter-gatherers. Proceedings of the National Academy of Sciences 104:4765.

*Moses, M. E., and J. H. Brown. 2003. Allometry of human fertility and energy use. Ecology Letters 6:295-300.

Expanding the Wheel?: Lotka's Max Power Principle and Human Ecology

A lot of blogs are about the most current and hottest new research published in a given field. For the blog to be interesting they have to get to it before most other people, often posting on papers that aren't yet released to the public. Or that's one approach anyway.

Going to another extreme, this is about a paper published in 1922 in PNAS by the influential physicist Alfred Lotka. The paper is titled "Contribution to the energetics of evolution." It's been cited thousands of times (unfortunately none of the citation indexes I have access to go back far enough to see how many) but I wonder what proportion of the people citing it have read it. A pdf of the paper is posted under week 12 (see sidebar to right). Yes it would have fit last week's theme better, but work with me here... It may alter the way you think about the world or you may just find it an interesting bit of science history - to read such an important paper that was published 85 years ago, count 'em, that's a lotta years.

The paper argues that a physical property underlies evolution by natural selection - the maximum power principle. A fairly concise view of the principle is given by the following quote:
"In every instance considered, natural selection will so operate as to increase the total mass of the organic system, to increase the rate of circulation of matter through the system, and to increase the total energy flux through the system, so long as there is presented an unutilized residue of matter and available energy.
This may be expressed by saying that natural selection tends to make the energy flux through the system a maximum…”

The point usually emphasized in the literature is this maximizing of flux through the system.

At the end of the paper, Lotka briefly ponders the relevance of his principle for an understanding of human evolution:
"We have thus derived, upon a deductive basis, at least a preliminary answer to a question proposed by the writer in a previous publication. It was there pointed out that the influence of man, as the most successful species in the competitive struggle, seems to have been to accelerate the circulation of matter through the life cycle, both by ‘enlarging the wheel,’ and by causing it to ‘spin faster.’ The question was raised whether, in this, man has been unconsciously fulfilling a law of nature, according to which some physical quantity in the system tends toward a maximum. This is now made to appear probable; and it is found that the physical quantity in question is of the dimensions of power, or energy per unit time…”

Lotka's views were echoed by a lot of later researchers who attempted to take a more thermodynamic view of human evolution - like Leslie White, Richard Adams, and Joseph Tainter. And were also applied to general biological phenomenal such as the evolution of body size (see Brown, Marquet, and Taper, The American Naturalist, 1993).

Its a classic and thought-provoking paper that should be read by everyone.

best,
Oskar

A breakthrough view of modern hunter gatherer societies

With Regards: Myra & David

Week 12: Scaling (part 1)

Required Readings
*Brown, J. H. 2002. The fractal nature of nature: power laws, ecological complexity and biodiversity. Philosophical Transactions: Biological Sciences 357:619-626.
*Gibson, C. C., E. Ostrom, and T. K. Ahn. 2000. The concept of scale and the human dimensions of global change: a survey. Ecological Economics 32:217-239.
*pages 1771-1777 of Brown, J. H., J. F. Gillooly, A. P. Allen, V. M. Savage, and G. B. West. 2004. Toward a Metabolic Theory of Ecology. Ecology 85:1771-1789.

Optional
Schneider, D. C. 2001. The Rise of the Concept of Scale in Ecology. BioScience 51:545 – 553.

Energy and "Cultural Development" in the US

I'm posting this as a new entry rather than as a comment to the Week 11 post in order to include graphs.

White (1943) presents a very simple model of energy use and cultural development, E X F = P, where E is per-capita energy, F is efficiency of energy use, and P is productivity or the "degree of cultural development". The US Government, through the Energy Information Administration, provides just the data we need to get a picture of how this has worked in the US economy for the past nearly 60 years.

This first graph is P, "the total amount of goods or services produced" as measured by Gross Domestic Product, corrected for inflation by being expressed in year 2000 dollars. There has been some skepticism expressed in class that real wealth has been increasing in the US over the past several decades, so this figure should lay that myth to rest. Average real wealth has increased nearly 3 and a half times over the time span represented.


The next graph features E, per-capita energy use. Notice the increasing trend until the oil shocks of the early 1970's, after which per-capita energy consumption has remained statistically constant.


If we're not buying increased production through increased energy use, White's model predicts we're doing so through an increase in efficiency. This can be seen in the next figure, which graphs F, the productivity gained per unit use of energy.


While efficiency was increasing slowly before the oil shocks, the pace picked up in the 1970's, efficiency doubling in the years since 1973. This increase in efficiency shows up through more "efficient" use of pollution, as the next figure shows. The amount of greenhouse gases produced to generate each dollar of wealth has fallen significantly over the past quarter century for which we have data.

Week 11: Energetics, culture, and society

These papers discuss the importance of energy in governing the dynamics and self-organization of complex systems. Howard .P. Odum, Leslie A. White, Boltzmann , Schrodinger (Schrödinger 1992), and Lottka (Lotka 1922) were some of the pioneers in researching the importance of energy in biological and human systems. Such scientists have sought to develop general principles of complex systems and evolution, often framed within the context of thermodynamics. Odum has had a profound influence in several scientific fields, including ecological economics, ecosystem ecology, general systems theory, ecological modeling, environmental engineering, and education. Tim F.H. Allen has been an important thinker in the development of ecological theory (e.g., Allen 1992). However, many of the ideas in these papers have yet to be rigorously developed and tested. In your writings for this week try to:

(1) carefully evaluate their reasoning and mechanistic explanations

(2) describe connections between these authors' ideas and other papers in the course

(3) and think of ways that these ideas could be built into more testable hypotheses.

Jordan

Please read the following for the coming week:

* White, L.A. 1943. Energy and the evolution of culture. American Anthropologist 45: 335-356.

* Odum, H.T. 1988. Self organization, transformity, and information. Science 242: 1132-1139.

* Tainter, J.A. et al. 2003. Resource transitions and energy gain: Contexts of organization. Conservation Ecology 7:  4 - 17.

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Additional references

Allen, T. F. H. 1992. Toward a Unified Ecology. Columbia Univ Pr.

Lotka, A. J. 1922. Contribution to the Energetics of Evolution. Proceedings of the National Academy of Sciences 8:147-151.

Schrödinger, E. 1992. What is life? Cambridge Univ. Press.

Follow-up on discussion, week 10

Hey!
Great discussion on Thursday. There was definitely a lot more fodder for discussion than we could get into in just that class period.

A few notes:
Fred mentioned, in regard to the example about schooling behavior in fish, that just because you show that the emergent phenomena could result from localized and 'blind' interactions doesn't mean that you actually have shown it. While I think the school thing is still a good example of an emergent phenomenon, her comment points directly to one of the biggest issues in the use and interpretation of agent based models. You can give agents rules and tweak parameters until you get all kinds of different patterns. Once you've demonstrated that your model can generate a pattern like the one you're interested in, can you conclude that you've therefore explained it? (there is a tendency for modelers in this area to act as if generating the 'right' pattern with a set of rules is the same as explaining it). Not only could lots of different types of localized interactions, based on different rules and parameter values, potentially generate the same pattern but other external or top down controls might still be relevant even though the model generates a pattern without them. This creates a difficult situation for the use of such models but a lot of applications have shown that you can make more refined empirical predictions, which can in turn be tested with additional observation or fieldwork. Lansing's work may be the very best example of this in the social sciences. Keep in mind that the paper we read was from 1993 and he has done a lot of stuff since then. Check out his website if you're interested.

Als0 relevant to the Lansing and Kremer paper is the issue of agency. We all seemed to take some kind of issue with the contrast between 'blind' and 'deliberate' selection and what roll human agency played in Bali temple networks. I'm not sure we resolved this in class but we came up with at least two types of possible interpretation: 1) we disagree with Lansing and Kremer and think that they have shown the opposite of what they say they've shown - that blind localized interactions generate the temple network and that you don't need to invoke some special human agency at all - but that depends on what you think agency is. 2) that if you 'read between the lines' of their paper they are actually disagreeing with how a lot of anthropologists use the concept of agency and they are just doing so in a careful and stealthy way. It is most likely the case that they are making the point that the agricultural system falls apart without conscious human action, not at the level of the whole system but in terms of intentionally maintaining and managing plots of land, whereas other 'natural' systems presumably don't require this explicit planning. This would assume that human planning is qualitatively different from the planning done by say, a beaver. Agency can be a bit of a slippery concept. Regardless of these issues of interpretation, that this complex social structure could be generated as a 'self-organized' process of neighbor-to-neighbor communication is hugely important, provocative, and definitely not a typical variety of anthropological explanation.

I also liked how we kept finding more linkages between the papers the more we talked about them. Perhaps in the early days before the establishment of the temple networks and the social structures they help maintain, there would have been more problems of synchronization as the system was in more of an 'r' rather than a 'K' phase, as Paul pointed out. Maybe shrimp aquaculture is not so well-organized or structured and top-down controls are necessary to keep it from going chaotically out of control? We could attempt to categorize these issues and others with respect to Holling's phases to see if we are able to gain insight via application.
Have a great weekend. We'll be posting more shortly...
Oskar