Archive for evolution
February 27, 2011 at 1:13 PM · Filed under evolution, metaphors, semantics
Even before Darwin authored “On the Origin of Species” he used variants of the term ‘selection’ to describe the (now well-known) theory of evolution by natural selection. In the 19th century England, ‘selection’ was in common use among animal and plant breeders who isolated desirable variants and bred them for future generations. Darwin appropriated the term as an analogy and an appeal to experiences grounded in everyday life. Darwin’s ‘natural means of selection’ was a tactic to deal with the cultural inertia of teleology – supernatural design explanations for the emergence of species. The term stuck, and it continues to resonate – in part because ‘natural selection’ is an extension of human desires and not those of other species.
Following publication of “On the Origin of Species”, Darwin went on to reconsider his use of ‘natural selection’ to describe the evolutionary process. In letters to Asa Gray and Charles Lyell on the 26th and 28th September, 1860, respectively, Darwin suggested that ‘natural preservation’ would be less confusing for some readers. He also hoped it might discourage related uses he found objectionable and inconsistent with the meaning he sought.
In 1866, Alfred Russell Wallace wrote to Darwin describing the difficulties that ‘natural selection’ posed to acceptance of the theory. Wallace argued that ‘natural selection’ was “indirect and incorrect”; Wallace thought ‘extermination’ rather than ‘selection’ was more appropriate to the evidence. It is evident that Wallace preferred personification as a rhetorical tactic, but he also recognized that people often took the metaphors too literally. He cited use of ‘Nature’ as a personification and begs for caution in Darwin’s rhetoric.
When Wallace wrote to Darwin about his use of ‘natural selection’, he pointed out how other contexts (e.g. watching, choosing, preferring, seeking, thought, direction) led to some of these anthropomorphic and voluntarist biases. Darwin’s pervasive anthropomorphic, voluntarist description of natural selection is described in depth by Young (1985) who elucidates Darwin’s contemporary milieu. Darwin appropriated ‘selection’ to reach across disciplines. He was seeking clarity in the processes he was trying to explain. In drawing on breeding culture, he found a ready example from everyday life to equate his theory with. Breeding, being a subset of natural selection, would provoke visual comparisons in people’s minds. Young points out another benefit of using ‘selection’ was that, in breeder’s terms, it simply differentiated their understanding of variation into known and unknown causes (Young p95). Darwin was just trying to imply that he had expanded what was known about the causes of variation in nature.
In his 1866 letter, Wallace’s ultimate goal was to convince Darwin to replace his ‘natural selection’ with Herbert Spencer’s term ‘survival of the fittest’. This was suggested to obviate the invocation of an external actor ‘selecting’ among individual variants. Darwin largely ignored Wallace’s suggestion, but he put the phrases ‘natural selection’ and ‘survival of the fittest’ into direct competition in his reply to Wallace:
The term Natural selection has now been so largely used abroad & at home that I doubt whether it could be given up, & with all its faults I should be sorry to see the attempt made. Whether it will be rejected must now depend “on the survival of the fittest”. As in time the term must grow intelligible, the objections to its use will grow weaker & weaker. I doubt whether the use of any term would have made the subject intelligible to some minds, clear as it is to others; for do we not see even to the present day Malthus on Population absurdly misunderstood.
Dawin went even further and inserted the term into the 5th edition of “On the Origin of Species.” Unfortunately, ‘survival of the fittest’ turned out to be fairly resilient and has led to a great deal of misunderstanding – in part because it became equated ‘natural selection’ which Darwin had not intended.
Young (1993) sums it up nicely:
“Natural selection – Darwin’s metaphor – needn’t therefore embarrass us now, because it’s allowed. It’s allowed once again to acknowledge the purposiveness, the final causes, the analogies to human intention, embedded in our concepts of and about nature. …the metaphorical nature of fundamental concepts in so-called basic sciences – affinity, gravity, natural selection – dissolves the barrier between scientific discourse and other modes of expression.” This makes one wonder what other metaphors would be just as productive – connecting to different modes of expression across existing barriers.
Biologists are now caught between choosing to use the metaphor in its anachronistic form, refusing to see its metaphorical quality altogether, or using it to support teleological evolutionism.
Another possibility to to attempt to synthesize what we have learned since Darwin to apply ever more imprecise metaphors in the hope that they too will stimulate enough refraction in meaning to generate productive research questions.
References
Darwin Correspondence Project Database. http://www.darwinproject.ac.uk/entry-2930/ (letter no. 2930; accessed 5 September 2010)
Darwin Correspondence Project Database. http://www.darwinproject.ac.uk/entry-2931/ (letter no. 2931; accessed 5 September 2010)
Darwin Correspondence Project Database. http://www.darwinproject.ac.uk/entry-5140/ (letter no. 5140; accessed 5 September 2010)
Darwin Correspondence Project Database. http://www.darwinproject.ac.uk/entry-5145/ (letter no. 5145; accessed 5 September 2010)
Young, R. M. (1985). Darwin’s Metaphor. Cambridge University Press. pp92-112.
Young, R.M. (1993). Science as Culture (no. 16) 3 :375-403.
September 23, 2010 at 3:41 PM · Filed under community interaction design, complex systems, design ecology, energy, evolution, futures, heterarchy, interaction, preferences, relational aesthetics, service design, symbolic systems, technology
A Simple Model of Attachment
The image above was the first draft. This is the second. Thanks to Aliya for good, perceptive comments.
attachmentModel_v2
Premises:
Culture as the processes that allow the uptake of processes, procedures, information, beliefs, values and social norms.
Cultural affiliations are attachments.
Attachments and reattachments are limited (quantity) and constrained (quality) by pressures.
Aspiration is a cultural step in creating capability.
Based in part on: Appadurai, A., 2004, ‘The Capacity to Aspire: Culture and the Terms of Recognition’, in Rao, V. and Walton, M., (eds.) Culture and Public Action, Stanford University Press, Palo Alto, California, pp 59-84.
July 13, 2010 at 4:16 AM · Filed under architecture, biology, community interaction design, complex systems, Design, design ecology, evolution, interdisciplinary, network entrepreneurship
Mountains and Landscapes as Heuristics
In the 1930s, evolutionary geneticist Sewall Wright pulled together research strands in the biology of inbreeding, the genetics of coat color in guinea pigs, statistical methods (including path analysis), and mathematics that codified the changes in gene frequencies in populations as a result of natural selection, mutation, and migration.
His resulting description of these threads set the stage for qualitatively different perspective on the evolutionary process. Wright described his perspective as a “shifting balance” model of evolutionary change, and it highlighted the role of small populations in the transitions between periods of high and low fitness. This pattern, which followed from his use of the term “drift”, describes the fluctuations of gene frequencies that result from the random sampling of small populations. This random sampling comes from mating in small populations that, because of chance, produces small deviations from the numbers of genes originally represented in the population.
Wright’s Shifting Balance perspective coincided with his introduction of the adaptive landscape as a term to describe the space in which random fluctuations of gene frequencies in small populations could push the populations away from adaptive peaks or periods in which they were reproductively successful, and which would in turn allow natural selection to push them towards new adaptive peaks – areas of differential reproductive success.
Though Wright’s perspective on evolution is controversial (in a generative way), the perspectives and tools that emerged from his ideas have endured. For example, Wright’s work preceded algorithmic approaches to optimization problems in mathematics, networks (traveling salesman), metallurgy (simulated annealing), and artificial intelligence – to name a few
The process of Shifting Balance is described as a series of three dynamic phases:
Phase 1, the exploratory phase, the action of small groups explores new combinations. Most stay on the suboptimal fitness peak (reasonably successful), but some get caught in adaptive valleys (unsuccessful).
In Phase 2, selection causes the groups that are in the adaptive valleys to move toward new, higher-fitness peaks.
Finally, in phase 3, groups at higher fitness peaks send off migrants helping other groups move to higher fitness peaks.
Phase 1: The Exploratory Phase
Phase 2: The Selection Phase
Phase 3: The Migration Phase
While Wright’s process was intended for population genetic systems, an increasing convergence between social processes, cognitive psychology, technology, ecology, and creative practice suggests that the concepts apply well to the exploratory, form-finding processes that precede the design and production of materials and services. The implementation of the Shifting Balance process as a analog for social and creative strategy is useful for the production of highly original and robust creative solutions – or, at least it’s a testable hypothesis.
For some, analogies between biological and social processes are difficult to comprehend. However, the design of services and interactions is dependent on the ordering and reordering of processes, materials, people, and ideas. Combinations and recombinations of these things, when developed thoroughly and communicated, can impact the delivery and relational aspects of individuals working in cooperation or separately.
We could envision this process as a sort of charette (period of intense design in collaborative groups) activity where:
- The exploratory phase initiates adaptive schema (creative combinations) which are driven by the interactions, specializations, and diverse perspectives of small groups;
- Intergroup selection resulting from evaluation, the inherent heterogeneity among groups, and intended service platforms begins the iterative process of amplification of good combinations;
- Export and translation of valuable forms/schema to other groups in order to test them against different problems, social contexts for cooperation, and consumptive patterns.
The immediate benefit of this strategy is the demonstration of expertise in practice, the role of discourse, and the chance events that can drive innovation. Participants from different disciplines will have to opportunity to observe and engage in creative problem solving within highly diverse communities. Here the focus is on collaborative ideation followed by problem-solving across disciplinary and expertise-based boundaries and ultimately an exercise in cooperative translation, storytelling, and communication.
There is enough social scientific research to at least point to the benefit of diverse groups, although it would be worthwhile to have a better handle on an ideal number – i.e. what counts as a small population. Plus, how do we go about choosing? What is the process of selection…or should we instead be saying, “What is the process of attachment?” And finally, are there specific patterns of translation or dissemination that we should aim for? For if migrants endowed with the most successful schema do disperse and link up with others, they have an opportunity to cooperate and raise the capacity the other groups elsewhere. But through which mechanisms to we initiate and implement these processes?
There are a few other ideas that seem uniquely coupled to the Phases of Shifting Balance. An example is the goal of participation as a unique form of empowerment in community planning exercises. One particular model of participatory engagement provided by Conde et al. (2004) is used in the context of climate change planning (below).
The Landscape of Participation
This example shows transitional categories in participation. When viewed through a model of culture which emphasizes process over characteristics, these are skills acquisition categories that indicate differences with an impact on fitness – i.e. reproductive success.
Each category represents a different level of engagement, a level that itself suggests a tighter relationship between participants and the tools of participation or cooperation.
- Informative participation is an exchange of information, which may or may not be meaningful.
- Consultation requires that participants begin asking questions as well as providing information.
- Functional engagement means that different participants identify and agree to share goals, thus ordering their actions in accordance with each other.
- Interaction means the initiation of feedback, where signals and shifts in the participation is met with responsiveness and dialog with the others.
- Self-motivated participation is demonstrated by the points at which processes are acquired and reorganized by the participants themselves.
- Migration ultimately expands the instances of participation which have been successful, sharing them with other communities, and finding cooperative allies elsewhere.
References:
Conde, C., Lonsdale, K., Nyong, A., & Aguilar, I. (2004). Engaging stakeholders in the adaptation process. Adaptation policy frameworks for climate change: Developing strategies, policies and measures, 47–66.
Johnson, N. (2008) Sewall Wright and the development of shifting balance theory. Nature Education 1(1)
Wright, S. (1977) Evolution and the Genetics of Populations. Vol. 3: Experimental Results and Evolutionary Deductions. University of Chicago Press, Chicago.
June 13, 2010 at 10:07 AM · Filed under architecture, biology, boundary objects, cognitive justice, cybernetics, design ecology, evolution, futures, preferences, sexual selection
This post consists of some notes that looking at the analogy of natural & artificial selection to design and its consequences. A worthwhile paper on a related but different topic is Christina Cogdell’s Products or Bodies? Streamline Design and Eugenics as Applied Biology (2003) Design Issues, 19(1), 36-53. doi:10.1162/074793603762667683
Types of Selection
The purpose of this page is to describe how natural selection can be used as a framing tool for recognizing how artifacts, services, and interventions can affect individuals and natural populations of humans and other species. The point is not to draw a direct analogy, but to try to link the effects of the things we make to the behaviors, growth, and flourishing of living things. These are not so much set rues as they are a set of guides that can help us reconsider the expected effects of changing our environment in order to evaluate the risk and alternative future possibilities involved in the production of technology from the most precursory to the most complex.
I was intrigued after a reading group discussion we had about anthropometrics. Wikipedia defines anthropometrics as the measurement of human to gather statistical data about the distribution of body dimensions in the population are used to optimize products. I would alter this definition slightly to say design products rather than optimize. Humans change and so do products.
We were a little unsettled by the focus only on human needs and the intent that anthropometry be entirely in support of comfort and ease of use. Taking a more critical approach, we started to brainstorm all of the different ways that design structures human and non-human behavior. We started to keep an eye open for ways that design and evolution can begin to interact. We hit some dead ends so I reached out.
I asked a group of colleagues if they knew of any comprehensive taxonomy of selection, and here is what one of them (Joel) contributed:
There are so many different ways to split selection up that it can be mind-boggling. To make it worse, those who study molecular evolution use different terms (positive, balancing) than those of us who study phenotypic selection. I don’t think there’s a way to taxonomize the terms satisfactorily, at least in a tree. It would probably look more like a convoluted Venn diagram.
That said, Joel laid out four areas that can be used to focus our attention. I’ve modified them from his interpretation, but they are basically agents, episodes, modes, and scales.
Here is how he originally wrote about it in his response to me:
In the phenotypic selection realm, I tend to split selection up in four different ways, based on agents, levels, fitness components, and mode.
The agent of selection, that is, the factor that causes fitness differences to arise, can be either ecological (phyisical or heterospecific) or conspecific. I would call the former ecological selection and the latter social selection (sensu West-Eberhard). The latter would tend to subsume sexual selection, which tends to be caused by male-male or male-female interactions. Includes frequency-dependent and density-dependent or other x-dependent.
The level of selection describes the units that exhibit fitness differences (which, annoyingly, Gould call “agents” of selection). This can be individual selection, and at higher levels, family selection, group selection, kin selection, social selection (sensu Wolf, Moore, and Brodie), etc. Hard and soft selection can fall under this category as well–Wade and Goodnight have good papers discussing this.
Third, selection can be split into different “episodes” by splitting total fitness into multiple components. This is usually done because it is empirically convenient, or to examine evolutionary trade-offs. This gives rise to terms like survival selection, fecundity selection, and sexual selection.
Finally, you can describe selection based on the shape of the fitness surface, i.e. the “mode.” This includes directional (linear), stabilizing, disruptive, and correlational (all three quadratic). Of course, the shape of the fitness surface is often complex, and you can have elements of all of these going on at once when you’re considering multiple traits.
Reframing Selection
We might think about what Joel said differently and transform it as the grammatical structure of a sentence. Where:
AGENT = SUBJECT
SELECTION =VERB
EPISODE = DIRECT OBJECT
MODE might be akin to diagramming the entire sentence. while SCALE is more like the context that the sentence takes place within (e.g. the paragraph or passage).
Agents
Agent refer to the most causal explanation for the response to selection. Agents provide the mechanistic explanation and frequently are the antagonists to the entity/entities experiencing the effects of selection.
From a designer’s perspective, these agents should be the artifacts or services we create either with the intent to exert some selective force or ameliorate it.
We can understand these as ecological agents that affect anything from the climate of our surroundings, our food supply, the structure or our living and working spaces, interactions with outer species (as in pets, disease, or domesticated laborers), and even perhaps to our conventional definitions of time that enable further articulations of the environment.
Similarly social agents work along the lines of our own perception, learned, and innate behaviors to enumerate male-male, male-female, family, and cooperative interactions. Sensation and display are extremely important because they distinguish among individuals to allow decisions about how to interact. Social agents range from clothing, jewelery and other status symbols to weapons, traditions, and business plans as agents of cooperation or competition.
There is a nice hybrid space too where ecological and social meet in the production of artifacts favoring or disfavoring reproduction–in vitro fertilization on one hand…and condoms on the other, for example.
Often, agent-based selection is described as selecting for trait ‘x’ and can even be more complicated when traits x, y, and z covary as a result of this selection. As a consequence we find that selection can be multi-facited and not reducible to a single interaction. Hence, we need to reconsider the cumulative effects of each agent’s contribution.
Episodic
Moving along the causal chain (if we can indeed identify it), we would then want to understand the factors or physical attributes that are on the receiving end of the agents’ work. From an empirical perspective, this is often where conflict begins and fluctuates in an ever-present set of trade-offs. We can split the effects into many different components looking at reproduction, lifespan, health, outlook, social status, niche, range, communicativeness, and, perhaps most importantly, agency (as the ability of an individual to act as its own agent).
This is the main point of interest in design–i.e. what, where, when do the effects of the design work manifest in nature?
Mode and Variance
In order to understand what patterns are present, evolutionary biologists look at variation and the response of a particular trait or episode to selection from agents. Here attention is focused on the values of the entire population in contrast to just the trait itself. We can certainly use these visualizations and modes to describe the distributions of episodic traits, but here there is explicit quantitative emphasis on the response to selection over one or more generations.
We can think about it in different ways: populational and interactional or hard and soft.
Populational
Populational patterns include the ideal types of directional (linear), stabilizing, disruptive, and correlational (all three quadratic), and null (no selection). The shape of the fitness surface is often complex, and you can have elements of all of these going on at once when you’re considering multiple traits.
This graph depicts four abstract types of natural selection. The colors are used only to differentiate between types. The axes show the proportion of individuals in the population as a function of their trait values through time.
The graph below is composed of four of these types where the axes show the proportion of the population as a function of trait values through time. The shaded areas represent the part of those populations that is being selected for. The color simply differentiates between types. Correlational selection is not shown because it consists of the interaction of multiple traits in response to selection, and we would need a 3-dimensional graph to show just two of those traits changing.
From the graph you can see the response of a population to null selection. Because mutation-based variation is not selected out of the population, the shape of the distribution randomly changes and will not fit a “standard” distribution.
The blue, directionally-selected distributions move (you guessed it) directionally because of pressure against one end of the distribution.
Likewise, stabilizing selection in green is like directional, but instead of one end the pressures are exerted to stabilize the mean.
For diversifying (aka disruptive) selection in red, the mean is selected against–leaving greater proportions near the previous tails of the distribution.
Interactional
The second way is what I call interactional, meaning it depends on the interactions among agents, often in space. Here, ecological agents and social agents exert their effects. The goal of this description is to capture the meaning behind the mechanism (thus, interaction) rather than the change over time. When coupled with population visualization techniques, one begins to get a dynamic picture of evolutionary change.
We may be able to consider correlational selection as a special case of interactional (and not populational) because the internal constraints within a population’s gene pool and genomic regulation are effectively a suite of internal genetic interactors at a different scale.
Normally however, we can think of interactional patterns in terms of frequency-dependence, density-dependence, or some other x-dependent factor related to ecological or social agents. So frequency-dependence, for example, is just a way of describing the total effect of agents…or of saying that the trait in question responds in a way that is frequency-dependent.
The main difference is that interactional describes the mechanism of selection itself (within a generation), while populational describes the response to selection (change between generations).
Putting the two together means we could graph dynamic change.
Hard
Both hard selection and soft selection are relative to the population as a whole. Hard selection is like a bat chasing an insect. The insect has some maximum speed that it can flee and the bat has some speed that it can chase. Assuming it is only the bat and the insect, then there is hard selection for the speed at which the insect can flee.
Soft
Of course insects are probably not alone since they tend to aggregate in large populations. Soft selection takes this into account and considers the effect of more than one insect fleeing. Here the insect needs not be faster than the bat, just faster than the other insects that the bat is following!
The major difference is one of absolute value or of percentage. Hard selection works on the absolute value of a trait while soft selection works on a percentage of the distribution of trait values.
Scale
The scope of impact of a particular service of artifact is also important, especially when we ask the question, “for whom?” Is it working on a emergent trait or even creating one? Examples might include political systems or policies that increase or decrease emmigration, the locating of a hazard that increases mutation rates, or one child policy.
Whereas before we were only considering a single ideal population, what happens when we include multiple populations? Does the work of the designer or design team affect traits that span across individuals and include qualities that can only be formed from collective-action?
Some levels of scale might include: individual, family, kin, group, social, community, or ecological.
June 13, 2010 at 8:15 AM · Filed under art, evolution, symbolic systems, visual culture
If you are willing to accept some non-human based research in pursuit of the human, you might find these helpful. They have a pretty heavy biological and philosophical bent to them. Some like Gablik, Miller, Darwin, and Dissanyake provide pretty sweeping theories for the evolution of art and design (with varying levels of detail and different forms of evidence). Others deal mainly with theory and
research derived from observation of non-human animals. Still others use social science and humanities based approaches to the question (Loos/Danto (with Gablik replying in ‘progress in art’), Bergson, Luhmann). Also see Bobbi S. Low’s cite for what may be the only scientifically testable prediction in the bunch.
Donath, J.S. Signals, Truth and Design. MIT Press, Cambridge, MA, forthcoming.
Burke, E. 1757. A philosophical enquiry into the origin of our ideas of the sublime and beautiful. R. and J. Dodsley, London.
Endler, J. A. 1992. Signals, signal conditions and the direction of evolution. American Naturalist 139:S125-S153.
Gablik, S. 1976. Progress in Art. Rizzoli International Publications, Inc., New York.
Kirkpatrick, M. 1982. Sexual selection and the evolution of female preference. Evolution 36:1-12.
Miller, G. F. 2001. Aesthetic fitness: How sexual selection shaped artistic virtuosity as a fitness indicator and aesthetic preferences as mate choice criteria. Bulletin of Psychology and the Arts 2:20-25.
Ryan, M. J. 1990. Sensory systems, sexual selection, and sensory exploitation. Oxford Surveys of Evolutionary Biology 7:157-195.
Scheib, J. E., S. W. Gangestad, and R. Thornhill. 1999. Facial attractiveness, symmetry, and cues of good genes. Proceedings of the Royal Society of London B 226:1318-1321.
West-Eberhard, M. J. 1979. Sexual selection, social competition and evolution. Proceedings of the American Philosophical Society 123:222-234.
Loos, A., & Opel, A. (1997). Ornament and Crime: Selected Essays. Ariadne Press (CA).
Ellen Dissanayake, Art and Intimacy: How the Arts Began (Seattle: University of Washington Press, 2000),
Christy, J. H., and P. R. Y. Backwell. 1995. The Sensory Exploitation Hypothesis. Trends in Ecology & Evolution 10:417-417.
Laland, K. N. 1992. A Theoretical Investigation of the Role of Social Transmission in Evolution. Ethology and Sociobiology 13:87-113.
Miller, G. 2000. The Mating Mind: How Sexual Choice Shaped the Evolution of Human Nature. Doubleday, New York.
Nettle, D. and H. Clegg. Schizotypy, creativity and mating success in humans. Proc. R. Soc. B (2006) 273, 611–615
Kavolis, V. Community Dynamics and Artistic Creativity. American Sociological Review, Vol. 31, No. 2. (Apr., 1966), pp. 208-217.
Luhmann, N. Art as a social system. Stanford University Press. Stanford, Calif. 2000.
Network Theory—the Emergence of the Creative Enterprise. Albert-László Barabási. Science 29 April 2005:Vol. 308. no. 5722, pp. 639 – 641
Low, Bobbi S. 1979. Sexual selection and human ornamentation. In Chagnon, Napoleon A., and William Irons, eds., 462-87. – describes a test of sexual selection for art as the comparison of stable versus unstable symbolic systems
Danto, A. C. 1986. The Philosophical Disenfranchisement of Art. Columbia University Press, New York.
Darwin, C. 1871. The descent of man, and selection in relation to sex. John Murray, London.
Endler, J. A., and A. L. Basolo. 1998. Sensory Ecology, Receiver Biases, and Sexual Selection. Trends in Ecology & Evolution 13:415-420.
Lenski, R. 1999. A Distinction Between the Origin and Maintenance of Sex. Journal of Evolutionary Biology 12:1034-1036. -distinguishes between the orgin and maintenance of sexual reproduction
Turney J. (2004). THE ABSTRACT SUBLIME: Life as information waiting to be rewritten. Science as Culture, 13, 89-103. Retrieved July 17, 2008, from
http://www.ingentaconnect.com/content/routledg/csac/2004/00000013/00000001/art00004
Dissanayake, E.: What Is Art For? Seattle, University of Washington
Press (1988)
Dissanayake, E.: Homo Aestheticus : Where Art Comes from and Why. 1st University of Washington Press ed. Seattle, University of Washington Press (1995)
Healy, S., & Braithwaite, V. (2000). Cognitive ecology: a field of substance? Trends in Ecology & Evolution, 15(1), 22-26.
Bergson, H. (2005). Creative Evolution. Cosimo Classics.
Ryan, M. J., Phelps, S. M., & R, A. S. (2001). How evolutionary history shapes recognition mechanisms. Trends in Cognitive Sciences, 5(4), 143-148. Retrieved July 17, 2008, from http://www.sciencedirect.com/science?_ob=ArticleURL&_udi=B6VH9-42PC695-G&_user=10&_rdoc=1&_fmt=&_orig=search&_sort=d&view=c&_acct=C000050221&_version=1&_urlVersion=0&_userid=10&md5=7e622bb148b27c4cbf3d290d0a790563
Arak, A., & Enquist, M. (1995). Conflict, Receiver Bias and the Evolution of Signal Form. Philosophical Transactions: Biological Sciences, 349(1330), 337-344.
Endler, J. A., & Basolo, A. L. (1998). Sensory ecology, receiver biases and sexual selection. Trends in Ecology & Evolution, 13(10), 415-420.
Jansson, L., & Enquist, M. (2003). Receiver bias for colourful signals. Animal Behaviour, 66(5), 965-971. Retrieved July 17, 2008, from http://www.sciencedirect.com/science?_ob=ArticleURL&_udi=B6W9W-49J8TBN-J&_user=10&_rdoc=1&_fmt=&_orig=search&_sort=d&view=c&_acct=C000050221&_version=1&_urlVersion=0&_userid=10&md5=d7fd52368874c927aac68023a8029efd
Scourfield, J., N. Martin, G. Lewis, and P. McGuffin. 1999. Heritability of social cognitive skills in children and adolescents. Br J Psychiatry 175:559-564.
June 7, 2010 at 2:17 AM · Filed under architecture, biology, complex systems, cybernetics, design ecology, ecology, evolution, futures, genomics, interaction, interdisciplinary
Disaggregation among natural and social scientific communities can lead to misunderstandings about the different components of disaster management and socio-ecological systems. Terms like resilient, adaptive, robust are often used to describe systems and their processes and come up in the literature, policy, and the media very frequently. They have catch my attention because they have different use patterns in the field I know a little about: biology.
Adaptation, coping, resilience, and robustness have similar definitions, but they sometimes have different technical definitions across disciplines. Their different meanings contribute to their value, and they highlight the differences in perspectives that each scientific community contributes. However, the details matter for distinguishing important components of systems and what aspects might be suggestive for new insights or that might be responsive to intervention or assessment. It’s also important to establish common ground meanings when communities get together and work towards common goals.
There is a benchmark article Resilience, Adaptability and Transformability in Social–Ecological Systems that does a much better job at pulling together the literature than I do here, and I came across it after writing much of what is in this article. It is also the narrative used by the Resilience Alliance for their activities.
The following represents some of my notes and thinking as I try to sort out the definitions on my own. For me, it means asking how different perspectives contribute to the ways in which we interact in socio-ecological systems.
Adaptation
The Intergovernmental Panel on Climate Change (IPCC) 4th Assessment Report defines adaptation as:
Initiatives and measures to reduce the vulnerability of natural and human systems against actual or expected climate change effects. Various types of adaptation exist, e.g. anticipatory and reactive, private and public, and autonomous and planned. Examples are raising river or coastal dikes, the substitution of more temperature-shock resistant plants for sensitive ones, etc.
This definition takes its function from the ability of humans to manipulate their environment, making it better suited to human-identified goals and interests, even if acting on behalf of other organisms. Some synonyms include alteration, modification, redesign, remodeling, revamping, reworking, reconstruction, conversion, adjustment, acclimatization, acclimation, accommodations, habituation, acculturation, assimilation, and integration.
Adaptation is also used to describe genetically-accumulated evolutionary change over time in organisms as a response to natural selection. This is different from the case where manipulating the environment substitutes in the short-term replaces the pressure of genetic adaptation over the long term.
So I suppose this is why it calls to mind a version of evolution based on characters acquired in its lifetime (commonly known as Lamarckian inheritance)–if only for the appropriation of the term adaptation to refer to intra (within) generational processes and not inter (between) generational processes.
Adaptation for evolutionary biologists typically means processes through which a population becomes better suited to its environment over the course of many generations, often through natural selection. A great deal of debate and research has been directed at how we recognize adaptation in hindsight. This is because it can be difficult to state the causes for the evolution of a trait when we do not have direct observation and only historical signatures to learn from. Most notably this was discussed in “The Spandrels of San Marco”, a paper by Stephen Gould and Richard Lewontin (1979) that uses an analogy from architecture for the evolution of organismal form and function.
I agree that changing the environment in the ways mentioned in the IPCC definition will likely limit vulnerabilities for humans and other populations. However, there is an implicit assumption here that the goal should be for humans NOT to have to adapt over a course of generations–despite the inevitability of genetic change over time. It presupposes an assumption of stasis – and a very western one when compared to eastern notions of change and mutability. Richard Nisbett catalogues how some of these assumptions about change and stasis in his book The Geography of Thought. For me, it depends on what time scale one is looking to understand if stasis or change is more relevant. Still, I think its difficult to argue anymore that stasis is more relevant than change.
The necessary question should not be IF we should adapt (genetically or by manipulating the environment). Instead we should ask, “What are we adapting to and how are we getting there?” Will humans and other populations be adapting to artificially-supported ‘vulnerability balloons’ as we are almost surely doing now through our uses of technology and fossil fuels?
This question of adaptive goal is important because the IPCC definitions include definitions of costs and benefits with its description of adaptation. To what goal are these costs and benefits applied? Within the frame of a generation or an organism’s lifetime, explicating goals may make sense, but ascribing goals to a ecosystem – much less whole populations – gets very very slippery. You start to need some way to implicate who or what is writing that mission statement.
Similarly the IPCC includes adaptive capacity in its glossary as the ability, institutions, and resources that can be used to implement adaptation measures.
I think this is all a bit confusing, and I feel it makes more sense to reserve the definition of adaptation for genetic, phenotypic, and behavioral attenuation of organisms or systems to their environment across generations. To describe the processes that organisms and systems use during their lifetimes I think we need a term that encompasses more variability, one that is less blatantly anthropocentric and functionalist in its approach to socio-ecological coevolution. We also need a long view on systems not ones that are limited to single generations only – something that the biological definition of adaptation retains but that the socio-technical one does not.
Borrowing from the literature of evolutionary biology, behavior, and developmental biology, plasticity seems far better suited to the processes of environmental manipulation being described by the IPCC. This is because it references a material (plastic) that maintains its basic molecular structure while having variable capacity to take on any number of manipulations or forms.
Coping and Plasticity
The terms coping and adaptation are sometimes used interchangeably leading to confusion. Here I think there is some opportunity to disentangle the two. A compilation of brainstorming sessions by groups of development practitioners in Ghana, Niger and Nepal described some differences which were then documented in the Climate Vulnerability and Capacity Analysis Handbook. The results of the group’s sessions were pointing to what I think was a difference between 1) consistent and conscious actions to reduce vulnerability (adaptation) versus 2) ad hoc solutions (coping).
It’s worthwhile to differentiate coping and adaptation as within and between generation processes, respectively. Biologists use plasticity to describe the ability of an organism or group to adjust within its lifetime via behavioral or developmental responses to the environment. This may indeed include manipulation of the environment to decrease vulnerability. Phenotypic plasticity is a description that could easily encompass artifacts, behaviors, institutions, and aggregations of resources as extensions of an organism’s phenotype. It invokes important concepts from evolutionary biology including the role of cooperation in building and maintaining extended phenotypes (such as aggregations of useful materials like insurance, band-aids, and water) or how phenotypic reaction norms can change in response to different environments–shedding light on why a strategy in one environment may not be as successful in another. There is further correspondence here with plasticity and the concept of developmental canalization (that organismal systems can get locked in to specific trajectories) and with the concept of path dependence in the development of economic and institutional systems.
So a better definition of plasticity might re-appropriate the IPCC’s definition of adaptation and rework it as:
An adjustment in natural or human systems in response to actual or expected climatic stimuli or their effects, which moderates harm or exploits beneficial opportunities. Plasticity operates through cognitive (sensing), social (interactional), physiological, and other mechanisms that can adjust to a wide range of variability. Plasticity is the ability to respond to variability and a range of realized and possible futures continuously and in a sustained approach. Plasticity or coping strategies attenuate the use of resources to local needs and involve planning that hybridizes old and new knowledge and strategies in an exploratory process.
Here I think this definition makes it much easier to bridge what may be happening at a physiological level (cellular temperature variation, sweating) with responses at an artifact level (clothing, ventilation) and an institutional (e.g. policies towards what it means to be cool).
This is because the term plasticity explicitly invokes a connotation of variability, while adaptation feels more like a description of how well two things (in this case organism or population and environment) fit together. Clearly, if the environment is highly variable we need variability in our systems, not assumptions and values of how well we already fit and work within it.
Coping, on the other hand, seems pretty straightforward. Survive. It makes sense to leave a lot of variability open for this one, because when it comes time for coping strategies, any and all tactics may be appropriate. But then again, there can be ways to cope that are more responsive than others. But I think this starts to dig into a definition of resilience or robustness, where the system properties begin to matter more than than how they manifest themselves in practice. What I mean by this is that as people, organisms, and ecosystems attempt to cope with change, their ability to draw on networks or strategies for coping is itself embedded in the system. Some systems, as a function of their structure, cope better than others. Consequently the adapt better than other too.
Resilience
The Climate Vulnerability and Capacity Analysis Handbook adapts its definition from UNISDR (2009) defining resilience as “the ability of a system to resist, absorb, and recover from the effects of hazards in a timely and efficient manner, preserving or restoring its essential basic structures, functions, and identity.”
The IPCC defines resilience as “the ability of a social or ecological system to absorb disturbances while retaining the same basic structure and ways of functioning, the capacity for self-organisation, and the capacity to adapt to stress and change.”
While Walker et al (2004) define resilience as “the capacity of a system to absorb disturbance and reorganize while undergoing change so as to still retain essentially the same function, structure, identity, and feedbacks.”
In these cases resilience emphasizes a system’s ability to maintain or return to specific structural or functional features–i.e. to maintain its identity, its durability, its persistence. But as noted by Erica Jen in her article “Stable or Robust? What’s the Difference?” (2005), the choices of features or structural elements that we attend to are important for assessing both the capacity and quality of that responsiveness to change.
So what is the function, what is functional, and for whom? Definitions matter.
One way to think about resilience is to imagine a couple of different water balloons. One balloon is filled halfway full. Another is filled so that the latex rubber that composes its surface and membrane is stretched tightly to hold the water in. Now you can throw both balloons back and forth between each other, and neither may pop. But what do you think will happen when the balloons are stretched, twisted, or allowed to drop on the ground where a twig might be a hazard to the already tense surface of the overfilled balloon? It will probably pop and spill the water out.
A system’s resilience is a lot like a water balloon, and the degree of resilience is determined by how much water is forced into the balloon, the size of the balloon, and how much it is pushed to its limits. We might think of the balloons shape, its ‘throwability’ or the thickness of its membrane as examples of functional or structural elements. In most cases, we are looking at how well the balloon is able to maintain it shape and its continuity despite being stressed – i.e. it is functionally a ‘water balloon’, it has a round shape, and responds to the exterior and interior pressures of air and water.
Rarely do we think that a water balloon might reconfigure itself, rearranging the organization of its functions, structural elements, or features to be able to accomplish the same task differently. What would happen if the water and the balloon separated or if the water balloon system was able to draw on other systems (e.g. refrigeration) to change the relationships between its functional elements? What if we no longer simply considered only the water inside of the balloon as the system responding to the task of throwing? What if the throwing and catching movements were also included? Would we still think of a resilient system, or would we start to walk a path of robustness–of being able to adjust the definitions and constraints of the systems themselves in pursuit of coevolutionary relationships between them?
Robustness
Robustness is a different beast altogether – literally. While resilience is focused on maintaining a system, we can describe robustness as the ability of a system to change and in doing so to respond to environment and to develop entirely new functions as a result.
Some argue that robustness describes the ability of a system to withstand mutations and maintain its phenotype or “shape” as a result (Wagner, 2005). Instead I think there is a greater correspondence of robustness with transformation as used by Walker et al (2004). Transformability is “the capacity to create a fundamentally new system when ecological, economic, or social (including political) conditions make the existing system untenable.” I’m less sure about the “untenable” part of Walker et al’s definition.
Robustness is the ability of a system to evolve system functions, not simply maintain those that already exist. In this way, an analogy can be drawn between adaptation/robustness and plasticity/resilience. Similarly, I think robustness has a quality of being parametric. Parametric architecture has the quality of being built from common construction principles, but by varying the parameter values of those rules of construction, endless forms become possible.
References
Walker, B., C. S. Holling, S. R. Carpenter, and A. Kinzig. 2004. Resilience, adaptability and transformability in social–ecological systems. Ecology and Society 9(2): 5. [online] URL: http://www.ecologyandsociety.org/vol9/iss2/art5
UNISDR, 2009. Terminology: Basic terms of disaster risk reduction and IISD et al, 2007. Community-based Risk Screening – Adaptation and Livelihoods (CRiSTAL) User’s Manual, Version 3.0.
Climate Vulnerability and Capacity Analysis Handbook
http://www.careclimatechange.org/index.php?option=com_content&view=article&id=25&Itemid=30
IPCC, 2007: Climate Change 2007: Impacts, Adaptation and Vulnerability. Contribution of Working Group II to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change, Annex I., M.L. Parry, O.F. Canziani, J.P. Palutikof, P.J. van der Linden and C.E. Hanson, Eds., Cambridge University Press, Cambridge, UK, 976pp.
Stephen Jay Gould and Richard C. Lewontin. “The Spandrels of San Marco and the Panglossian Paradigm: A Critique of the Adaptationist Programme” Proc. Roy. Soc. London B 205 (1979) pp. 581-598
Wagner, Andreas. 2005. Robustness and Evolvability in Living Systems (Princeton Studies in Complexity). Princeton University Press.
Nisbett, R. E. (2004). The Geography of Thought: How Asians and Westerners Think Differently…and Why. Simon and Schuster.
July 25, 2008 at 8:04 PM · Filed under cognitive justice, community interaction design, critical theory, evolution, metaphors, semantics
I’m picky when it comes to using metaphors. They reveal so much about the biases and commitments that underscore our thinking and, more importantly, how that thinking gets translated into physical manifestations and action.
Cathy Davidson at HASTAC has written a sharp brief on the use of the word ‘selection’ as it pertains to evolution and natural selection. She writes,
Having spent a day pulling book after book after book off my shelf, and looking at the proforma and obligatory evolutionary argument that almost inevitably comes in the final chapter of an otherwise careful description and discussion of brain functionality, I am convinced that the word “selection” has a lot to answer for.
The point she makes in the article is that the use of the word selection is directly linked to ideology. I think she is right here, and it should have been incumbent on the evolutionary biology community to recognize this and have proffered a solution early in its history. My fear is that, to do so, would be seen as a mocking retort to creationists that so recently cloaked their arguments in the guise of intelligent design. Well, maybe that a good thing.
Expanding on the relationship of the selection metaphor and its connection to ideology, Margret Evans, a psychologist at the University of Michigan, studies some of the ways that children, potential users of evolution, acquire evolutionist and creationist beliefs. Evans describes how Western religious and philosophical traditions emphasize essentialism, teleology, and intention, and in the process limit the cognitive appeal of natural explanations for the origins of species. She argues that because these ideas tend to show up repeatedly in public representations, they constrain the inferential reasoning capacities of the developing mind. It’s an observation that suggests science’s own predilection for categorization is at the root of evolutionary biology’s social friction.
Maybe we ought to have namethis.com come up with a new term.
March 17, 2008 at 10:49 PM · Filed under biology, ecology, evolution, heterarchy, host-parasite, interaction
This is actually a really old post from when I was doing my master’s work in host-parasite biology. Nonetheless, it turns out that I’m revisiting it in preparation for an upcoming project.
Behavioral differences between the sexes may explain sexually dimorphic patterns of infection. The risk of infection may be one such factor that an analysis of movement paths can predict. For example, if males spent more time than females foraging for food and, as a result, passively ingest more parasites while doing so, then their risk for infection would generally be greater than females. The tortuosity (or crookedness) of movement paths between the sexes were compared to see if any differences in movement (e.g. foraging) could suggest an explanation for male-biased infection. These differences may suggest that males and females experience their environment at different scales.
Image Analysis
The first thing that needs to be done is to plot the movement of the snails. This can be done by hand, but time-lapse digital photography can help to automate the process. The easiest way to do this was to set up a tripod with the camera pointed down. A white container was used to hold the snails and create the highest contrast background for the photography. Pay attention to the reflection of your light source on the surface between the subject and camera (in this case, water and plastic container). A picture was taken approximately every minute, and to make things simple for the analysis program, I used only two snails per trial- one female and one male. Once I had a stack of pictures (over the course of an hour or two), I loaded them into the image analysis program.
ImageJ is the java implementation of an image analysis program developed by the National Institutes of Health. ImageJ allows you to track the movements of individuals on the screen and outputs a list of XY coordinates for each subject. The first thing that had to be done though was to import the images as a greyscale stack. Once that was done, I cropped out the uninteresting parts of the frame to show only the subject of interest. Further processing was needed to create a binary (black/white) image source for the analysis. Using Process>Subtract Background, I created more contrast with the subject and background. Finally, using the Process>Binary>Threshold, I was able to make the stack be completely composed of black and white images with no greytones inbetween. This is crucial if the analysis algorithm is going to separate the subject from the background. Some parameters may need adjusting for optimal results, but it usually works without too much toying. The final step in ImageJ is to apply the Plugin “Tracker”. This plugin tracks the subject(s) on the screen and outputs a datafile with the coordinates of the movement path. These can then be saved into a text file for later use. I used only two individuals per trial because Tracker is limited to only two subjects. A plugin called MultiTracker is available, but I found it difficult to keep it focused on both individuals. When individuals overlap in space MultiTracker assigns both sets of coordinates to a single individual.
Movie 1. Male and female movement played back after image processing and before tracking analysis.
Measuring the Fractal Dimension of the Paths
I found a great program for measuring the fractal dimension (D) of the snail movement paths. This measurement is thought to measure the scale at which an organism percieves its landscape. Differences in D for different populations would suggest that the populations utilize their landscape differently- perhaps as a result of their perception. The program for measuring D is called Fractal (Nams 2003), and it allows you to import the XY coordinates (after you pare them down to the basic data in excel or something like it). It also allows you to do this as a batch process, making large datasets more manageable. Fractal will give you D for your sample along with confidence intervals. I used a paired-sample t-test in my final analysis. It turned out to be important that I paired similar individuals in the trials; the results did indicate a positive relationship between D and body length. Luckily, I put males and females of the same size in each trial. You’ll have to look into the guidelines for using Fractal yourself if you are going to take a stab at it, but the descriptions are pretty easy to follow. With a bit of doing, it shouldn’t pose a problem to measure these types of behaviors yourself.
A comparison of movement paths for a male and female in maps generated by Fractal.
Selected Bibliography
Bascompte, J., C. Vila. 1997. Fractals and search paths in mammals. Landscape Ecology 12:213-221.
Dicke, M., P. A. Burrough. 1988. Using fractal dimensions for characterizing tortuosity of animal trails. Physiological Entomology 13:393-398.
Escos, J. M., C. L. Alados, J. M. Emlen. 1995. Fractal structures and fractal functions as disease indicators. Oikos 74:310-314.
Nams, V. O. 1996. The VFractal: a new estimator for fractal dimension of animal movement paths. Landscape Ecology 11:289-297.
Nams, V. O. 2001. Using animal movement paths to measure response to spatial scale. submitted.
Turchin, P. 1996. Fractal analyses of animal movement: A critique. Ecology 77:2086-2090.
With, K. A. 1994. Using fractal analysis to assess how species percieve landscape structure. Landscape Ecology 9:25-36.
December 5, 2007 at 11:47 PM · Filed under biology, complex systems, Design, ecology, ecoregionalism, evolution, host-parasite
One of the questions that’s been nagging at me is if the CEMA lab that we’ve been building is an applied testing ground for Science, Technology and Society (STS) Theory and Practice. Wikipedia describes Science and technology studies (STS) as:
the study of how social, political, and cultural values affect scientific research and technological innovation, and how these in turn affect society, politics, and culture.
My interpretation is surely unidimensional, and I’m sure there are many examples of experimental media arts and technology spaces where critical questions are being addressed. Are there programs that take a specifically empirical approach to the propositions that come from STS and its metaview of science as it is practiced? Many of CEMA’s projects look at how technology and scientific enterprise are embedded in society and politics. Because we specifically implement creative art & design practices in the process, we seek to generate multidimensional perspectives that can further stimulate the ways in which artifacts are designed, situated, and discussed in culture and society. One of these outcomes may be so-called innovation. My curiosity leads me to wonder if the structures that STS identifies can be tested.
A recent article in Design Issues looked at how products and practices are linked under actor-network theory. The authors, Jack Ingram, Elizabeth Shove, and Matthew Watson, suggest that their concepts have the potential to bridge design and social theory. Studying processes of acquisition, specialization, scripting, appropriation, assembly, normalization and practice can lead one to recognize how artifacts, processes, and principles are tightly linked. These linkages may or may not lead to what Malcolm McCullough calls ‘deskilling’ – where individuals and their environment become increasingly estranged as infrastructural bias accumulates.
I suppose this is why I am excited about one of our students’ projects. Prayas Abhinav has created Not Alone, which is more or less the Indian implementation of TXTmob. TXTmob was successfully used during the Democratic and Republican National Conventions for protesters to actively coordinate their movements and demonstrations. One of the interesting questions to come out of this is how the implementation of this very socio-political technology will fare in India. What concerns and questions need to be addressed? I think Prayas is taking an interesting tactic by formulating the distribution of Not Alone as a form of social intervention designed to aid those in need.
What’s interesting to me is how technologies and scientific structures can be compared across landscapes to reveal how large-scale ecosociopolitical trends shape the differences in how technology and science are practiced and interpreted. Shelia Jasanoff took this approach in her book, Design on Nature, when she compared different conceptions for when life “begins” in the US, UK and Germany. By showing how the differing legal and political approaches led to the formation of different definitions of life, she showed how abortion issues reproductive rights are scripted and normalized (my interpretation).
So I’m thinking about all of this because I have long been interested in male-biased infection patterns which are especially prevalent in affluent countries. I started thinking about these patterns and how they might relate to Malcolm’s description of ‘deskilling.’ Are biological relationships like those between host and parasite affected and influenced by infrastructure and artifacts degrading or biasing over time? Is this a ratcheting effect and, if so, is it at all similar to the ratchet effect experienced by asexual populations as they diminish genotypic variation each generation through selection? Do landscape effects like the differences in infrastructure in the U.S. versus India contribute to this? hmmm…
March 26, 2007 at 4:13 PM · Filed under boundary objects, evolution, host-parasite, interdisciplinary, making it public, relational aesthetics, sculpture, teaching and learning, thesis
The exhibition of Sui generis continues this week in the Windows Room (3rd floor) at Palmer Commons (hours: 7:30 am-11pm Mon-Sat). The exhibition is open to the public now through April 13th, 2007.
A reception will be held on Friday, March 30th from 5-6:30 p.m. at the above location. Gabriel Harp will be on hand to discuss the work.
A presentation entitled, “Network Entrepreneurship in Biology, Art, & Design” will take place on April 2nd, 2007 from 5-6:30 p.m. in the Art & Architecture Auditorium.
About the work:
Sui generis is a large-scale tectonic, systems-based installation designed to take into account related conceptual attributes of a chapel, scientific laboratory, carnival, and children’s nursery. Sui generis offers a cognitive retreat, a place for reflection, and a chance to come into close physical proximity with other organisms and ourselves. A rules-based activity based on the concept of asexual reproduction continues through the duration of the exhibition. A selection from Lewis Carrol’s Through the Looking Glass often used to explain and ideate contemporary theories about the evolution of sex and recombination accompanies the artwork.
In order to experience the installation, visitors will be invited to raise their heads through one of the two holes in the floor underneath. When inhabiting the interior, the two viewers will be confronted not only with the shadowscape, but also with each other. As the architecture is elusive in its source, it invites diverse interpretations–a carnival sideshow, a Zen garden, a Victorian greenhouse, a virus, or perhaps even a flower awaiting pollination.
The title Sui generis indicates an idea, an entity or a reality that cannot be included in a wider concept. In intellectual property law, exclusive rights are granted for the creation and development of plant breeds, databases and traditional knowledge (among others) to reflect that the subject matter is a product of the intellect.
For more background, explore a database of terms and concepts associated with the design of Sui generis as well as documentation of the construction process.
About the Artist:
In his work, Gabriel Harp recombines visual art and life science (epistemology) through the processes of critical design and network entrepreneurship. Often working at the interfaces of evolutionary biology, bioinformatics, education, and visual culture, his work investigates the roles of metaphors in education, science and policy and the primacy of visual signals in the discourse surrounding genomics and biotechnology. Collaborating with Zack Denfeld and others, Gabriel is currently developing a visual map of patent claims on the human genome.
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