Saturday, January 20, 2007


Evolution - The hitchhiker's guide to altruism

Darwin explained how beneficial traits accumulate in natural populations, but how do costly traits evolve? In the past, two theories have addressed this problem.

The theory of hitchhiking suggests that genes that confer a cost to their bearer can become common in natural populations when they "hitch a ride" with fitter genes that are being favored by natural selection. Conversely, the theory of kin selection suggests that costly traits can be favored if they lead to benefits for relatives of the bearer, who also carry the gene.

"Animal traits are not always independent. For example, people with blond hair are more likely to have blue eyes," explains Andy Gardner (Oxford University). "This is a nuisance for natural selection, which could not, for instance, favor blond hair without also indirectly favoring blue eyes, and this is the idea of genetic hitchhiking."

Kin selection is similar, but here the genetic associations are between different individuals: "If I have a gene that makes me more altruistic, then I can also expect my relatives to carry it. So while the immediate effect of the gene is costly for me, I would benefit by receiving altruism from my relatives, and so the gene is ultimately favored," Gardner explains.

New research carried out at the University of Edinburgh and Queen's University, Canada shows that both processes are governed by the same equations. This reveals that kin selection can be seen as a special form of genetic hitchhiking, explain Gardner and his coauthors Stuart West and Nick Barton (University of Edinburgh) in the February issue of The American Naturalist.

The researchers built on a general framework for modeling hitchhiking first proposed by Barton and colleagues, showing how it can be used to describe social evolution and recovering the classical results of kin selection theory. This insight raises the possibility of using the tools of hitchhiking theory to explore social problems that have so far been too complicated to analyze using traditional kin selection techniques. [Source: University of Chicago Press]


Based on The American Naturalist paper:

Am Nat. 2007 Feb ;169 (2):207-26 17211805
The Relation between Multilocus Population Genetics and Social Evolution Theory.
Andy Gardner, Stuart A West, Nicholas H Barton


Evolution at multiple gene positions is complicated. Direct selection on one gene disturbs the evolutionary dynamics of associated genes. Recent years have seen the development of a multilocus methodology for modeling evolution at arbitrary numbers of gene positions with arbitrary dominance and epistatic relations, mode of inheritance, genetic linkage, and recombination. We show that the approach is conceptually analogous to social evolutionary methodology, which focuses on selection acting on associated individuals. In doing so, we (1) make explicit the links between the multilocus methodology and the foundations of social evolution theory, namely, Price's theorem and Hamilton's rule; (2) relate the multilocus approach to levels-of-selection and neighbor-modulated-fitness approaches in social evolution; (3) highlight the equivalence between genetical hitchhiking and kin selection; (4) demonstrate that the multilocus methodology allows for social evolutionary analyses involving coevolution of multiple traits and genetical associations between nonrelatives, including individuals of different species; (5) show that this methodology helps solve problems of dynamic sufficiency in social evolution theory; (6) form links between invasion criteria in multilocus systems and Hamilton's rule of kin selection; (7) illustrate the generality and exactness of Hamilton's Rule, which has previously been described as an approximate, heuristic result.


In this article, we highlight the social evolutionary interpretation of this multilocus methodology. In particular, we show how the quantitative genetical approach is exactly analogous to existing methodology used for social evolutionary problems and that it provides a straightforward guide to constructing and analyzing social evolutionary models of arbitrary complexity. Moreover, we demonstrate that multilocus theory may be used to solve problems of dynamic sufficiency in social evolution models so that we may examine coevolutionary dynamics of social evolutionary traits and describe the evolution of relatedness itself. We emphasize that no new methodology is developed but rather that this article is intended as a synthesis of multilocus and social evolution theory so that the results derived within each of these bodies of theory may be readily interpreted in terms of the other.


Recent posts:

"Why altruism paid off for our ancestors"

"Genetics of eye colour unlocked"

"History-hunting geneticists can still follow familiar trail"

"Sex ratios and social evolution ('Current Biology' article)"

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Learning the language of gene expression

Researchers have taken a major step towards understanding the language of gene regulation in the fruitfly Drosophila and they expect the technique to be rapidly applicable to understanding the effects of genome variation in humans.

The new research, published today in PLoS Computational Biology, is a major advance in using computers to detect the regions in DNA that control the activity of genes. Studies on single genes have shown that variation in gene regulation can be important in disease. The new program, called NestedMICA, allows researchers to find many regulatory regions, which will become a new focus for disease understanding.

The team, from the Wellcome Trust Sanger Institute and The University of Manchester, took slices of genome sequence from next to each Drosophila gene - where the highest concentration of regulatory signals are thought to lie - and fed them into the new computer program that looks for patterns shared between the sequences. The search process is similar to looking for words in a sentence where the vocabulary of the language is unknown.

"Most words in the language of gene regulation can be spelled more than one way," explained Dr Thomas Down, first author on the report. "In English, you might see people writing either 'analyse' or 'analyze'. In genomes, such variation - or even bigger differences - seems to be normal.

"So we can't just count words, we need to recognize alternative spellings."

The team, which includes Dr Casey Bergman from Manchester's Faculty of Life Sciences, has so far found 120 'words' - distinct examples of regions that might regulate genes. About 30 of these were known from many years of studying how individual Drosophila genes are controlled, but most are novel. This is a major step towards understanding the language of gene regulation in an important model organism, and proof of principle of a new technology that will speed the study of regulatory elements in the human genome. Drosophila is a well-studied organism and shares 48% of its 14,000 genes with humans.

Research emerging in the past few months suggests that variation in the sequence of regulatory regions will affect susceptibility to many diseases. A few cases are already known - one form of thalassaemia is caused by a regulatory sequence variant - but knowledge of regulatory elements in the human genome is limited: scientists have only scratched the surface.

Systematic annotation of regulatory regions in the human genome will be very important if researchers are going to understand the effects of all sequence variation.

Dr Tim Hubbard, senior author on the report explained: "While others have tried to identify these control regions before, they have had to try to align lots of sequences. Our new method doesn't depend on alignment, an advantage because the new program is robust to rapidly evolving sequences.

"The new method also doesn't require prior knowledge from, say, looking at known examples, and can search for hundreds of different motifs at once."

As science should, the work makes predictions that the team is testing. Using a set of excellent, publicly available data on gene activity from the University of California-Berkeley and Lawrence Berkeley National Laboratory, they have predicted what some of the newly discovered sequences might mean in the language of gene regulation.

Computer analysis can accelerate the search for important regions in genomes, but the authors emphasize that computer predictions must always be examined experimentally. The findings in Drosophila by the new program have been validated by examining findings against results from experimental imaging.

The results of the research, a set of Drosophila sequence motifs, are freely available from a database at the Sanger Institute. Like many tools developed at the Sanger Institute, NestedMICA is open source software, freely available for anyone to download, run and modify. (Source: University of Manchester)


Based on the open access/free paper:

Large-Scale Discovery of Promoter Motifs in Drosophila melanogaster

Thomas A. Down, Casey M. Bergman, Jing Su1, Tim J. P. Hubbard


A key step in understanding gene regulation is to identify the repertoire of transcription factor binding motifs (TFBMs) that form the building blocks of promoters and other regulatory elements. Identifying these experimentally is very laborious, and the number of TFBMs discovered remains relatively small, especially when compared with the hundreds of transcription factor genes predicted in metazoan genomes. We have used a recently developed statistical motif discovery approach, NestedMICA, to detect candidate TFBMs from a large set of Drosophila melanogaster promoter regions. Of the 120 motifs inferred in our initial analysis, 25 were statistically significant matches to previously reported motifs, while 87 appeared to be novel. Analysis of sequence conservation and motif positioning suggested that the great majority of these discovered motifs are predictive of functional elements in the genome. Many motifs showed associations with specific patterns of gene expression in the D. melanogaster embryo, and we were able to obtain confident annotation of expression patterns for 25 of our motifs, including eight of the novel motifs. The motifs are available through Tiffin, a new database of DNA sequence motifs. We have discovered many new motifs that are overrepresented in D. melanogaster promoter regions, and offer several independent lines of evidence that these are novel TFBMs. Our motif dictionary provides a solid foundation for further investigation of regulatory elements in Drosophila, and demonstrates techniques that should be applicable in other species. We suggest that further improvements in computational motif discovery should narrow the gap between the set of known motifs and the total number of transcription factors in metazoan genomes.


...Functional binding sites are likely to be subject to purifying selection and thus should exhibit a reduced rate of sequence evolution. This is based both on the observation of increased levels of conservation in known TFBSs relative to their background sequences and the intuition that losing elements responsible for gene regulation may often be deleterious. Of course this does not mean that all regulatory elements are under strict purifying selection, and indeed there are good examples of divergence in regulatory element function, as well as conservation of regulatory function with underlying binding site turnover at the sequence level. Nevertheless, increased conservation of predicted TFBSs provides evidence for functional constraint.

To test whether motifs in our set show signatures of evolutionary constraint among Drosophila species, we studied patterns of motif conservation in a large set of orthologous non protein-coding alignments...


Other papers:

1) From the journal Molecular Biology and Evolution:

Common Pattern of Evolution of Gene Expression Level and Protein Sequence in Drosophila

Full Text

Sequence divergence scaled by variation within species has been used to infer the action of selection upon individual genes. Applying this approach to expression, we compared whole-genome whole-body RNA levels in 10 heterozygous Drosophila simulans genotypes and a pooled sample of 10 D. melanogaster lines using Affymetrix Genechip. For 972 genes expressed in D. melanogaster, the transcript level was below detection threshold in D. simulans, which may be explained either by sequence divergence between the primers on the chip and the mRNA transcripts or by down-regulation of these genes. Out of 6,707 genes that were expressed in both species, transcript level was significantly different between species for 534 genes (at P less than 0.001). Genes whose expression is under stabilizing selection should exhibit reduced genetic variation within species and reduced divergence between species. Expression of genes under directional selection in D. simulans should be highly divergent from D. melanogaster, while showing low genetic variation in D. simulans. Finally, the genes with large variation within species but modest divergence between species are candidates for balancing selection. Rapidly diverging, low-polymorphism genes included those involved in reproduction (e.g., Mst 3Ba, 98Cb; Acps 26Aa, 63F; and sperm-specific dynein). Genes with high variation in transcript abundance within species included metallothionein and hairless, both hypothesized to be segregating in nature because of gene-by-environment interactions. Further, we compared expression divergence and DNA substitution rate in 195 genes. Synonymous substitution rate and expression divergences were uncorrelated, whereas there was a significant positive correlation between nonsynonymous substitution rate and expression divergence. We hypothesize that as a substantial fraction of nonsynonymous divergence has been shown to be adaptive, much of the observed expression divergence is likewise adaptive.

2) From the journal Science:

Sex-Dependent Gene Expression and Evolution of the Drosophila Transcriptome


Comparison of the gene-expression profiles between adults of Drosophila melanogaster and Drosophila simulans has uncovered the evolution of genes that exhibit sex-dependent regulation. Approximately half the genes showed differences in expression between the species, and among these, approximately 83% involved a gain, loss, increase, decrease, or reversal of sex-biased expression. Most of the interspecific differences in messenger RNA abundance affect male-biased genes. Genes that differ in expression between the species showed functional clustering only if they were sex-biased. Our results suggest that sex-dependent selection may drive changes in expression of many of the most rapidly evolving genes in the Drosophila transcriptome.


Recent posts include:

"A Fly's-Eye View of Evolution (Drosophila melanogaster)"

"Genetic Surprise Confirms Neglected 70-Year-Old Evolutionary Theory"

"European team unexpectedly finds clues to origin of life"

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Friday, January 19, 2007


Study revises understanding of primate origins

A new study led by a University of Florida paleontologist reconstructs the base of our family tree and extends its roots 10 million years, a finding that sheds new light on the origin and earliest stages of primate evolution.

Published online this week in the Proceedings of the National Academy of Sciences (PNAS) and featured on the cover of its January 23 print edition, the study offers compelling evidence that a group of archaic mammals called plesiadapiforms (please-ee-ah-dape-i-forms) are more closely related to modern primates than to flying lemurs, which previously had been proposed.

The two-part study examined specimens representing more than 85 modern and extinct species and provides evidence that plesiadapiforms are the most primitive primates. The team also discovered two 56-million-year-old fossils, the most primitive primate skeletons ever described.

"These fossil finds from Wyoming show that our earliest primate ancestors were the size of a mouse, ate fruit and lived in the trees," said study leader Jonathan Bloch, a vertebrate paleontology curator at the Florida Museum of Natural History. "It is remarkable to think we are still discovering new fossil species in an area studied by paleontologists for over 100 years."

Bloch discovered the new plesiadapiform species, Ignacius clarkforkensis and Dryomomys szalayi, just outside Yellowstone National Park in the Bighorn Basin with co-author Doug Boyer, a graduate student in anatomical science at Stony Brook University.

Ignacius previously was known to science only by skulls and isolated bones. Other scientists have proposed that the animal was not an archaic primate, but instead a gliding mammal related to flying lemurs. However, Bloch and his team debunked this idea based on an analysis of a more complete and well-preserved skeleton. The second species, Dryomomys, had a skull about the size of a grape with a body length of about 6 inches.

"The demise of the dinosaurs opened up ecological space for mammals to diversify, which they did - and quickly," Bloch said. "The Paleocene, about 65 (million) to 55 million years ago, is the time period between the extinction of the dinosaurs and the first appearance of a number of undisputed members of the modern orders of mammals."

Researchers previously hypothesized that plesiadapiforms may be the ancestors of modern primates, but this idea generated healthy debate within the paleontology community; Bloch's team is the first to offer strong phylogenetic evidence supporting it. The team analyzed 173 characteristics of modern primates, tree shrews, flying lemurs with plesiadapiform skeletons to determine which species were most closely related.

"This collaboration is the first to bring together evidence from all regions of the skeleton, and offers a well-supported perspective on the structure of the earliest part of the primate family tree," Bloch said.

Modern primates can be recognized by at least five characteristic features: relatively large brains, enhanced vision brought about in part by eyes that face forward, a specialized ability to leap, nails instead of claws on at least the first toes, and specialized grasping hands and feet. Plesiadapiforms have some but not all of these traits, and Bloch and his team argue that this group of early primates may have acquired these traits over 10 million years in incremental changes to exploit their environment.

Bloch said plesiadapiforms adapted to changes in flowering trees. As the trees evolved, the early primates became more efficient at utilizing their flowers, fruit and sap - and the insects attracted to these same food sources.

"Plesiadapiforms have long been one of the most controversial groups in mammalian phylogeny," said Michael J. Novacek, curator of paleontology at the American Museum of Natural History. "First, they are somewhere near primates and us. Second, historically they have offered tantalizing, but very often incomplete, fossil evidence. But the specimens in their study are beautifully and spectacularly preserved."

The team also includes anthropology professors Eric Sargis of Yale University and Mary Silcox from the University of Winnipeg.

Source: University of Florida


Based on the PNAS paper:

Jonathan I. Bloch, Mary T. Silcox, Doug M. Boyer, and Eric J. Sargis

New Paleocene skeletons and the relationship of plesiadapiforms to crown-clade primates

Published online before print January 17, 2007, 10.1073/pnas.0610579104


Plesiadapiforms are central to studies of the origin and evolution of primates and other euarchontan mammals (tree shrews and flying lemurs). We report results from a comprehensive cladistic analysis using cranial, postcranial, and dental evidence including data from recently discovered Paleocene plesiadapiform skeletons (Ignacius clarkforkensis sp. nov.; Dryomomys szalayi, gen. et sp. nov.), and the most plesiomorphic extant tree shrew, Ptilocercus lowii. Our results, based on the fossil record, unambiguously place plesiadapiforms with Euprimates and indicate that the divergence of Primates (sensu lato) from other euarchontans likely occurred before or just after the Cretaceous/Tertiary boundary (65 Mya), notably later than logistical model and molecular estimates. Anatomical features associated with specialized pedal grasping (including a nail on the hallux) and a petrosal bulla likely evolved in the common ancestor of Plesiadapoidea and Euprimates (Euprimateformes) by 62 Mya in either Asia or North America. Our results are consistent with those from recent molecular analyses that group Dermoptera with Scandentia. We find no evidence to support the hypothesis that any plesiadapiforms were mitten-gliders or closely related to Dermoptera.


Recent posts:

"Sexual Selection and the Evolution of Brain Size in Primates"

"Humans and Chimpanzees: Close But Not That Close.."

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Evolution, Interactions, and Biological Networks

An open access/free article from PLoS Biology:

Citation: Weitz JS, Benfey PN, Wingreen NS (2007) Evolution, Interactions, and Biological Networks. PLoS Biol 5(1): e11 doi:10.1371/journal.pbio.0050011

The study of networks has expanded rapidly over the last 10 years; networks are now widely recognized not only as outcomes of complex interactions, but as key determinants of structure, function, and dynamics in systems that span the biological, physical, and social sciences [1-4]. The "new science of networks" has introduced novel paradigms of systems behavior, including small-world structure [6], scale-free networks [7], and the importance of modularity [8] and motifs [9]. Some of these ideas have been transplanted into biology, and the results thus far are mixed but promising. Certainly, the study of biological networks has brought new opportunities for publication, yet much effort has been placed at discovering particular patterns in unexpected places-e.g., scale-free distributions in gene regulatory networks [10] - and these findings come with the caveat that similar patterns do not necessarily point to a common mechanistic origin [11]. Despite the many findings of power laws and hubs in biological systems, it is important to keep in mind that in biology, networks are not of interest solely (even primarily) for their abstract properties. So, if biologists working at the bench or in the field remain skeptical of what the study of networks can do for them and for their discipline, network scientists should not be surprised. These biologists want to know: what makes biological networks distinct and why should non-networkologists care?

As Dobzhansky famously noted, nothing in biology makes sense except in the light of evolution [12]. This is particularly true of biological networks, and we believe that the lens of evolution provides an exciting opportunity to link disciplines in ways that address fundamental challenges in biology. When mathematicians and physicists discuss the "evolution" of a network, they are often describing the dynamics by which a particular network structure grows and changes [13]. When biologists discuss the evolution of networks, they typically mean that fitness is network-dependent and selection acts to optimize across a landscape of networks [14]. Both definitions are useful, indeed complementary; the former focuses attention on possible dynamical origins for network structure [11] and the latter highlights the possibility that higher-level properties resulting from networks may be selected for [15,16]. Here we offer a third way to think about networks.

The central organizing principle in the study of networks is that interactions between elements in a complex system are heterogeneous. Some elements are connected to many others, some to very few, and interaction strengths and dynamics may vary widely. This is certainly true of the vast majority of biological systems. A primary consequence of these heterogeneous interactions is that patterns and properties emerge at different scales of organization from the interactions themselves. What is distinct about biological networks is that they arise as a result of evolution, with selection operating at the level of individuals and as a result of interactions between organisms.

We propose to think about networks within organisms as complex phenotypes interacting with other networks. When two organisms and their respective networks interact, the outcome at multiple scales will reflect game-theoretic and density-dependent interactions [17-19]. Further, such an approach provides a framework for assessing how higher-order properties (e.g., robustness or resistance to attack) may emerge under constraints imposed by other organisms. We focus our attention on three types of networks within organisms-regulatory networks, sensory networks, and resource delivery networks-and we leave aside the evolution of networks of organisms (e.g., syntrophic networks or food webs) for which the concepts of game theory and density dependence are already essential tools of analysis [20]. Our choice of examples takes aim at a central question in biology: how do organisms evolve and maintain complex and diverse functions?

To begin, consider the regulatory network of a temperate phage. Once inside a bacterial cell, a phage coopts its host's machinery and begins to modulate a system of promoters and pathways leading to cell lysis or integration [21,22]. Co-infections may occur, in which case another phage with a related but genetically distinct encoding of a regulatory network may be present. Networks that can function "optimally" in isolation may perform poorly (or be subject to exploitation) when mixed with competitors, as is the case of defective interfering particles [23]. Competition among regulatory networks may lead to selection for robustness, the development of strain immunity, or altered host control.

Sensory networks provide another example. Systems biology is only beginning to explore the strategies used by cells to function reliably using noisy machinery. Some emerging themes include digital logic, integral feedback, and limit cycles [24]. These paradigms are representative of systems that are intrinsically insensitive to noise. However, these paradigms do not address the unique challenge of accurately sensing environmental signals: namely that real changes in the signal must be reliably distinguished from fluctuations in the levels of network components. Further, these paradigms do not address how individual cells cope with the exchange of signaling molecules produced by other individuals that may be trying to regulate or maintain function in the environment or may be attempting to disrupt intentionally the function of other individuals. If we want to know how cells reliably integrate information from multiple signals, we should also be concerned with fluctuations induced exogenously by the presence of alternative networks, some operating with the same or similar signaling molecules, and some actively interfering with signaling.

Finally, consider physical delivery networks such as the root system of a plant or the branching structure of a tree. Both networks must provide structural support, facilitate the delivery of nutrients and water from soil to shoot, confer resistance against catastrophic embolisms, all while scaling up their components and connectivity from year to year [25]. Yet a tree will have diminished reproductive success if its branching/root structure confers enhanced functioning in isolation, but the structure is easily shaded out above ground or is out-competed below ground by the network of an adjacent tree.

Evaluating and searching for optimal network design involves more than just finding peaks in a fitness function. The suitability of a given network design must be considered in the context of alternatives. Networks in this light can be seen as strategies, in much the same way that rapid growth or efficient growth are alternative strategies for organisms competing for a common resource. Unlike peaks in a fitness function, the success of a strategy depends on how well it can out-compete other strategies when it is rare, as well as how well it can resist invasion by other strategies when it is common. Coexistence of multiple network structures in biological systems may well reflect these types of game-theoretic interactions.

If we are to develop an evolutionary ecology of networks then we should: (i) improve classification schemes for describing the microstates of networks; (ii) develop a more rigorous, and perhaps, system-specific understanding of permitted moves and trade-offs between networks; and (iii) use the principles of game theory and adaptive dynamics to consider how networks interact via their emergent properties. For regulatory networks, do features emerge primarily through gene duplication with subsequent neofunctionalization, what are the fitness and energetic costs of such duplication events, or are there other more complex processes at work [26,27]? For sensory networks, tradeoffs may involve limitation of the number or production of pathway components and therefore may be an implicit constraint to adding additional signaling cascades to sense distinct conditions/molecules. The study of resource delivery networks raises the question of allocation strategies when network components involve fixed costs, such as the investment of tissue and energy [28]. In all cases, we are confronted with a substantial challenge for theory: what is a meaningful level of granularity with which to describe a network that itself is a vast simplification of complex interactions?

Ecologists have long advocated the study of how interactions among individuals lead to ecosystem-level networks that, in turn, shape community assembly, stability, and robustness [20]. The availability of high-throughput data in molecular and systems biology suggests new opportunities for cross-disciplinary synthesis. What biological or ecological function does a network perform or mediate? How robust is network-associated function with respect to various types of noise? How does network structure influence and reflect the process of evolution? To answer these questions, it may prove essential to consider how organisms with a given type of network invade a system dominated by individuals of a given type or of a coalition of types, and if so, what systems-level properties emerge. Shifting the perspective of the questions we ask (and the framework in which we ask them) will ensure that network theory continues to play an integral role in furthering biological research.


Many thanks are due to Jim Damon, Peter Dodds, Simon Levin, Benjamin Mann, and Jack Morava for inspiring discussions and to Peter Dodds, Michael Federle, Ilya Fischoff, Siva Sundaresan, and two anonymous referees for many helpful comments on the manuscript.

References (many are full text)

1. Albert R, Barabasi AL (2002) Statistical mechanics of complex networks. Rev Mod Phys 74: 47-97.
2. Newman MEJ (2003) The structure and function of complex networks. SIAM Review 45: 167-256.
3. Strogatz SH (2001) Exploring complex networks. Nature 410: 268-276.
4. Newman MEJ, Barabasi AL, Watts DJ, editors (2006) The structure and dynamics of networks. Princeton (New Jersey): Princeton University Press. 624 p. (Amazon Astore UK | US)
5. Barabasi AL (2002) Linked: The new science of networks. Cambridge (Massachusetts): Perseus Publishing. 256 p. (Amazon Astore UK | US)
6. Watts DJ, Strogatz SH (1998) Collective dynamics of 'small-world' networks. Nature 393: 440-442.
7. Barabasi AL, Albert R (1999) Emergence of scaling in random networks. Science 286: 509-512.
8. Hartwell LH, Hopfield JJ, Leibler S, Murray AW (1999) From molecular to modular cell biology. Nature 402: C47-C52.
9. Milo R, Shen-Orr S, Itzkovitz S, Kashtan N, Chklovskii D, et al. (2002) Network motifs: Simple building blocks of complex networks. Science 298: 824-827.
10. Barabasi AL, Oltvai ZN (2004) Network biology: Understanding the cell's functional organization. Nat Rev Gen 5: 101-113.
11. Keller EF (2005) Revisiting "scale-free" networks. Bioessays 27: 1060-1068.
12. Dobzhansky T (1973) Nothing in biology makes sense except in light of evolution. Am Biol Teacher 35: 125-129.
13. Dorogovtsev SN, Mendes JFF (2002) Evolution of networks. Advances Phys 51: 1079-1187. (Amazon Astore UK | US)
14. Pfeiffer T, Soyer OS, Bonhoeffer S (2005) The evolution of connectivity in metabolic networks. PLoS Biol 3(7): e228-doi:10.1371/journal.pbio.0030228 doi:10.1371/journal.pbio.0030228.
15. Alon U (2003) Biological networks: The tinkerer as an engineer. Science 301: 1866-1867.
16. Harbison CT, Gordon DB, Lee TI, Rinaldi NJ, Macisaac KD, et al. (2004) Transcriptional regulatory code of a eukaryotic genome. Nature 431: 99-104.
17. Hofbauer J, Sigmund K (1998) Evolutionary games and population dynamics Cambridge (United Kingdom): Cambridge University Press. 351 p. (Amazon Astore UK | US)
18. Nowak MA, Sigmund K (2004) Evolutionary dynamics of biological games. Science 303: 793-799.
19. Geritz SAH, Metz JAJ, Kisdi E, Meszena G (1997) The dynamics of adaptation and evolutionary branching. Phys Rev Lett 78: 2024-2027.
20. Pascual M, Dunne JA, editors (2006) Ecological networks: From structure to dynamics in food webs Oxford (United Kingdom): Oxford University Press. 386 p. (Amazon Astore UK | US)
21. Ptashne M (2004) Genetic switch: Phage lambda revisited Woodbury (New York): Cold Spring Harbor Laboratory Press. 3rd edition 168 p. (Amazon Astore UK | US)
22. McAdams HH, Arkin A (1997) Stochastic mechanisms in gene expression. Proc Natl Acad Sci U S A 94: 814-819.
23. Bull JJ, Millstein J, Orcutt J, Wichman HA (2006) Evolutionary feedback mediated through population density, illustrated with viruses in chemostats. Am Nat 167: E39-E51.
24. Tyson JJ, Chen KC, Novak B (2003) Sniffers, buzzers, toggles and blinkers: Dynamics of regulatory and signaling pathways in the cell. Curr Opin Cell Biol 15: 221-231.
25. Tyree MT, Zimmerman MH (2002) Xylem structure and the ascent of sap Berlin: Springer. 2nd edition 283 p. (Amazon Astore UK | US)
26. Davidson EH, Erwin DH (2006) Gene regulatory networks and the evolution of animal body plans. Science 311: 796-800.
27. Wagner A (2005) Energy constraints on the evolution of gene expression. Mol Biol Evol 22: 1365-1374.
28. Enquist B, Niklas K (2002) Global allocation rules for patterns of biomass partitioning in seed plants. Science 295: 1517-1520.


An Eric Davidson post: "Developmental Biology: Special Issue on the Sea Urchin Genome"

A recent post: "Evolution of complexity in signaling pathways"

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Thursday, January 18, 2007


Bats in flight reveal unexpected aerodynamics

The maneuverability of a bat in flight makes even Harry Potter's quidditch performance look downright clumsy. While many people may be content to simply watch these aerial acrobats in wonder, Kenneth Breuer and Sharon Swartz are determined to understand the detailed aerodynamics of bat flight - and ultimately the evolutionary path that created it.

They have taken a major step toward that goal by combining high-resolution, three-dimensional video recordings with precise measurements of the wake field generated by the bats' wing movements. Their study, published in the journal Bioinspiration and Biomimetics, marks the first such measurements made in bats and highlights ways in which bat flight appears to differ from bird and insect flight. The results suggest the possibility that a novel lift-generating mechanism may be at work in bats and point to the highly maneuverable mammals as a model for tiny flying machines.

Breuer, a professor of engineering at Brown University, who studied mechanical aerodynamics earlier in his career, is particularly intrigued by bats because 'they can generate different wing shapes and motions that other creatures can't.

Continued at "Bats in flight reveal unexpected aerodynamics"


Based on the paper:

Direct measurements of the kinematics and dynamics of bat flight

Abstract/Full Text

Experimental measurements and analysis of the flight of bats are presented, including kinematic analysis of high-speed stereo videography of straight and turning flight, and measurements of the wake velocity field behind the bat. The kinematic data reveal that, at relatively slow flight speeds, wing motion is quite complex, including a sharp retraction of the wing during the upstroke and a broad sweep of the partially extended wing during the downstroke. The data also indicate that the flight speed and elevation are not constant, but oscillate in synchrony with both the horizontal and vertical movements of the wing. PIV measurements in the transverse (Trefftz) plane of the wake indicate a complex 'wake vortex' structure dominated by a strong wing tip vortex shed from the wing tip during the downstroke and either the wing tip or a more proximal joint during the upstroke. Data synthesis of several discrete realizations suggests a 'cartoon' of the wake structure during the entire wing beat cycle. Considerable work remains to be done to confirm and amplify these results.


A Proceedings of the National Academy of Sciences (PNAS) paper published April 2006:

Development of bat flight: Morphologic and molecular evolution of bat wing digits


The earliest fossil bats resemble their modern counterparts in possessing greatly elongated digits to support the wing membrane, which is an anatomical hallmark of powered flight. To quantitatively confirm these similarities, we performed a morphometric analysis of wing bones from fossil and modern bats. We found that the lengths of the third, fourth, and fifth digits (the primary supportive elements of the wing) have remained constant relative to body size over the last 50 million years. This absence of transitional forms in the fossil record led us to look elsewhere to understand bat wing evolution. Investigating embryonic development, we found that the digits in bats (Carollia perspicillata) are initially similar in size to those of mice (Mus musculus) but that, subsequently, bat digits greatly lengthen. The developmental timing of the change in wing digit length points to a change in longitudinal cartilage growth, a process that depends on the relative proliferation and differentiation of chondrocytes. We found that bat forelimb digits exhibit relatively high rates of chondrocyte proliferation and differentiation. We show that bone morphogenetic protein 2 (Bmp2) can stimulate cartilage proliferation and differentiation and increase digit length in the bat embryonic forelimb. Also, we show that Bmp2 expression and Bmp signaling are increased in bat forelimb embryonic digits relative to mouse or bat hind limb digits. Together, our results suggest that an up-regulation of the Bmp pathway is one of the major factors in the developmental elongation of bat forelimb digits, and it is potentially a key mechanism in their evolutionary elongation as well.

Associated article from the Howard Hughes Medical Institute:

A change in a single gene may be in large part responsible for the evolution of flight in bats, according to new studies by Howard Hughes Medical Institute researchers. The findings not only help explain the emergence of flight in these animals, but also illustrate how alterations in genes that govern development can lead to the abrupt, dramatic changes in body shape frequently seen throughout evolution.

The fossil record indicates that bats, the only mammals with powered flight, date back to the Eocene, an era that began approximately 55 million years ago. Notably, bat wing anatomy has not changed substantially over the past 50 million years - an observation that served as a starting point for the new work, which was published April 17, 2006, in an advanced online publication of the Proceedings of the National Academy of Sciences.

"We saw that the evolution of flight was quite sudden," said Lee A. Niswander, a Howard Hughes Medical Institute investigator at the University of Colorado Health Sciences Center who led the study. "That means there could be just a few key changes in limb development that resulted in more dramatic downstream consequences."

To find those key changes, Niswander and colleagues focused on the third, fourth, and fifth digits of the bat forelimb. These digits - equivalent to a human's middle, ring, and pinky fingers - are highly elongated and provide the support necessary for the wing membrane to be used for flight.

The group compared the embryonic development of bat forelimbs with that of bat hind limbs, which have much shorter digits than those in the wing. They also compared the bat forelimbs to mouse forelimbs so that they would have a similarly sized reference group.

During digit development in both species, cartilage cells (chondrocytes) divide and mature in areas called growth plates. The unique shape of the bat's forelimb is due to higher rates of both chondrocyte division and terminal maturation. Terminal chondrocyte maturation occurs in a part of the growth plate known as the hypertrophic zone, which is correspondingly larger in bat forelimbs than in mouse forelimbs. This difference in size, the researchers found, is due in large part to the expression of a single gene: bone morphogenetic protein 2, or Bmp2.

The researchers found that developing digits in the bat forelimb expressed more Bmp2 than those in either bat hind limbs or mouse forelimbs. The group tested several other genes associated with chondrocyte maturation, but didn't find differences in expression.

Then, Niswander and colleagues found that if they cultured a growing bat forelimb in a soup of Bmp2 protein, the hypertrophic zone was larger and the digits grew longer than forelimbs grown without extra Bmp2. Forelimbs cultured with a Bmp2 blocking protein, on the other hand, developed a smaller hypertrophic zone and shorter digits than those grown normally.

The group's findings have implications not only for bat evolution, but also for mammalian evolution in general.

"What we seem to see is punctuated changes in morphology over evolutionary time," said Karen E. Sears, the first author on the research, who is also at UCHSC. "Species will be in stasis for millions of years and then very quickly we get brand new species. That hints at just a few changes in key developmental genes."

That observation supports the theory of punctuated equilibrium, put forth in 1972 by Niles Eldredge and Stephen Jay Gould. Punctuated equilibrium states that evolutionary change is not gradual and geologically "slow"; instead, long periods of stability can be punctuated by periods of dramatic evolutionary change, and new species can appear relatively rapidly.

Other authors on the study are Richard R. Behringer, of the Department of Molecular Genetics at the University of Texas M.D. Anderson Cancer Center, Houston; and John J. Rasweiler IV, of the Department of Obstetrics and Gynecology, State University of New York Downstate Medical Center, Brooklyn.

Recent posts:

"New Research on the Co-evolution of Bats and Moths"

"Home and away: Bat uses magnetic compass for long flights"

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Skull suggests human-Neanderthal link

Anthropology: Humans continued to evolve significantly long after they were established in Europe, and interbred with Neanderthals as they settled across the continent, according to new research published this week in the Proceedings of the National Academy of Sciences (PNAS) USA.

Professor Joao Zilhao of the University of Bristol, Professor Erik Trinkaus of Washington University and colleagues in Europe compared the features of an early modern human cranium found in the Pestera cu Oase (the Cave with Bones) in southwestern Romania with other human samples from the period (the Late Pleistocene). Differences between the skulls suggest complex population dynamics as modern humans dispersed into Europe.

The different fragments of the reconstructed cranium - named Oase 2 - were found in a Late Pleistocene bone bed principally containing the remains of cave bears. They were recovered during a systematic excavation project directed by Professor Trinkaus and Professor Zilhao between 2003 and 2005.

Radiocarbon dating of the specimen produced only a minimum age (more than 35,000 years), but similarity in morphological traits with the Oase 1 human mandible - found in 2002 on the surface of the cave, adjacent to the excavation area, and dated to about 40,500 years ago - lead the team to conclude that the two fossils were the same age. These are the earliest modern human remains so far found in Europe and represent our best evidence of what the modern humans who first dispersed into Europe looked like.

By comparing it with other skulls, Professor Zilhao and colleagues found that Oase 2 had the same proportions as modern human crania and shared a number of modern human and/or non-Neanderthal features.

However, there were some important differences: apparently independent features that are, at best, unusual for a modern human. These included frontal flattening, a fairly large juxtamastoid eminence and exceptionally large upper molars with unusual size progression which are found principally among the Neanderthals.

Professor Zilhao said: "Such differences raise important questions about the evolutionary history of modern humans. They could be the result of evolutionary reversal or reflect incomplete palaeontological sampling of Middle Paleolithic human diversity.

"They could also reflect admixture with Neanderthal populations as modern humans spread through western Eurasia. This mixture would have resulted in both archaic traits retained from the Neanderthals and unique combinations of traits resulting from the blending of previously divergent gene pools.

"The ultimate resolution of these issues must await considerations of larger samples of European early modern humans and chronologically intervening specimens. But this fossil is a major addition to the growing body of fossil, genetic and archaeological evidence indicating significant levels of biological and cultural interaction between modern humans and the anatomically archaic populations (including the Neanderthals) they met along the way as they spread from Africa into Eurasia."

It is apparent that the Oase 2 cranium indicates there was significant modern human morphological evolution since the early Upper Paleolithic, the researchers conclude. Oase 2 is 'modern' in its abundance of derived modern human features, but it remains 'non-modern' in its complex constellation of archaic and modern features.

Source: University of Bristol UK PR "40,000-year-old skull shows both modern human and Neanderthal traits" 15 January 2007


Based on the PNAS paper:

Pestera cu Oase 2 and the cranial morphology of early modern Europeans
Erik Trinkaus et al.

Published online before print January 16, 2007, 10.1073/pnas.0610538104


Between 2003 and 2005, the Pestera cu Oase, Romania yielded a largely complete early modern human cranium, Oase 2, scattered on the surface of a Late Pleistocene hydraulically displaced bone bed containing principally the remains of Ursus spelaeus. Multiple lines of evidence indicate an age of {approx}40.5 thousand calendar years before the present ({approx}35 ka 14C B.P.). Morphological comparison of the adolescent Oase 2 cranium to relevant Late Pleistocene human samples documents a suite of derived modern human and/or non-Neandertal features, including absence of a supraorbital torus, subrectangular orbits, prominent canine fossae, narrow nasal aperture, level nasal floor, angled and anteriorly oriented zygomatic bones, a high neurocranium with prominent parietal bosses and marked sagittal parietal curvature, superiorly positioned temporal zygomatic root, vertical auditory porous, laterally bulbous mastoid processes, superiorly positioned posterior semicircular canal, absence of a nuchal torus and a suprainiac fossa, and a small occipital bun. However, these features are associated with an exceptionally flat frontal arc, a moderately large juxtamastoid eminence, extremely large molars that become progressively larger distally, complex occlusal morphology of the upper third molar, and relatively anteriorly positioned zygomatic arches. Moreover, the featureless occipital region and small mastoid process are at variance with the large facial skeleton and dentition. This unusual mosaic in Oase 2, some of which is paralleled in the Oase 1 mandible, indicates both complex population dynamics as modern humans dispersed into Europe and significant ongoing human evolution once modern humans were established within Europe.


A 2003 open access/free PNAS paper by Trinkaus et al:

Published online before print September 22, 2003, 10.1073/pnas.2035108100
PNAS | September 30, 2003 | vol. 100 | no. 20 | 11231-11236

An early modern human from the Pestera cu Oase, Romania


The 2002 discovery of a robust modern human mandible in the Pestera cu Oase, southwestern Romania, provides evidence of early modern humans in the lower Danubian Corridor. Directly accelerator mass spectrometry radiocarbon (14C)-dated to 34,000-36,000 14C years B.P., the Oase 1 mandible is the oldest definite early modern human specimen in Europe and provides perspectives on the emergence and evolution of early modern humans in the northwestern Old World. The moderately long Oase 1 mandible exhibits a prominent tuber symphyseos and overall proportions that place it close to earlier Upper Paleolithic European specimens. Its symmetrical mandibular incisure, medially placed condyle, small superior medial pterygoid tubercle, mesial mental foramen, and narrow corpus place it closer to early modern humans among Late Pleistocene humans. However, its cross-sectional symphyseal orientation is intermediate between late archaic and early modern humans, the ramus is exceptionally wide, and the molars become progressively larger distally with exceptionally large third molars. The molar crowns lack derived Neandertal features but are otherwise morphologically undiagnostic. However, it has unilateral mandibular foramen lingular bridging, an apparently derived Neandertal feature. It therefore presents a mosaic of archaic, early modern human and possibly Neandertal morphological features, emphasizing both the complex population dynamics of modern human dispersal into Europe and the subsequent morphological evolution of European early modern humans.


Recent posts mentioning Eric Trinkaus:

Tuesday, October 31, 2006 - "Romania: Cave Fossils indicate Humans and Neanderthals may have interbred"

Saturday, September 09, 2006 - "Modern Humans, not Neandertals, may be evolution's 'odd man out'"

Other recent Neandertal posts include:

Friday, January 12, 2007 - "Earliest Evidence Of Modern Humans In Europe Discovered By International Team"

Tuesday, November 28, 2006 - "Synchrotron Reveals How Neanderthal Teeth Grew"

More posts can be found by using the searchbox (top-left hand corner of this page)

Note some posts use the alternate spelling of "neandertals"

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Wednesday, January 17, 2007


Manatees Have 'Long-Distance' Sense of Touch

New research suggests that manatees' tactile sense is so finely tuned that the animals may experience 'touch at a distance' - an ability to 'feel' objects and events in the water from relatively far away.

In recent studies marine biologists Roger Reep and Diana Sarko at the University of Florida in Gainesville found that the giant mammals are covered with special whiskerlike hairs that act as sensors.

'We discovered that [manatees] have what are called tactile hairs all over their bodies, unlike most mammals, which just have whiskers on their faces,' said Reep, from the university's College of Veterinary Medicine.

Together these tactile hairs form a kind of sensory array, the biologists say, possibly allowing manatees to detect changes in current, water temperature, and even tidal forces.

...In a separate study (*see below) Reep and Sarko also found that manatees have more brain space dedicated to the sense of touch than other mammals do.

The research, published last month in the journal Brain, Behavior and Evolution, found that brain regions associated with touch are "especially large" in manatees - as large as or larger than in animals known to be particularly sensitive feelers, like star-nosed moles (**see below).

"That just reinforced our idea that [manatees] really are relying on their sense of touch to be able to navigate their world," Sarko said.

Full National Geographic article at "Manatees Have "Long-Distance" Sense of Touch, Experts Say"


*"Somatosensory Areas of Manatee Cerebral Cortex: Histochemical Characterization and Functional Implications"


A histochemical and cytoarchitectural analysis was completed for the neocortex of the Florida manatee in order to localize primary sensory areas and particularly primary somatosensory cortex (SI). Based on the location of cytochrome oxidase-dense staining in flattened cortex preparations, preliminary functional divisions were assigned for SI with the face represented laterally followed by the flipper, body and tail representations proceeding medially. The neonate exhibited four distinct patches in the frontoparietal cortex (presumptive SI), whereas juvenile and adult specimens demonstrated a distinct pattern in which cytochrome oxidase-dense staining appeared to be blended into one large patch extending dorsomedially. This differential staining between younger versus older more developed animals was also seen on coronal sections stained for cytochrome oxidase, myelin, or Nissl bodies. These were systematically analyzed in order to accurately localize the laminar and cytoarchitectural extent of cytochrome oxidase staining. Overall, SI appears to span seven cytoarchitectural areas to which we have assigned presumptive functional representations based on the relative locations of cytochrome oxidase-dense staining.


**Star-nosed mole - see the second part of New Research Shows Larval Fish Use Smell to Return to Coral Reefs (Video): "Moles, Shrews Can Smell Prey While Underwater"

A post on Manatees from Tuesday, August 29, 2006: "Manatee Bones Lead Stanford Scientist to New Insight on Evolution"

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Intelligent Design Video: 'Unlocking the Mystery of Life'

'Unlocking the Mystery of Life' (67 mins - Amazon Astore UK | US) - The scientific case for Intelligent Design - is produced by Illustra Media:

"Time, chance, and natural selection. Since Darwin, biologists have relied on such processes to account for the origin of living things. Yet today, this approach is being challenged as never before..."

The video starts with the 'landmark meeting' held by Phillip Johnson (TalkOrigins article on Phillip Johnson) in Pajaro Dunes California in 1993 and describes the development of the Intelligent Design movement through contributions from well-known names such as Paul Nelson, Stephen Meyer, Michael Behe, William Dembski, Jonathan Wells, and Scott Minnich.

Sample quotations from the 'Unlocking the Mystery of Life' video:

Phillip Johnson:

I sometimes wonder why anybody talks about anything else. Because this is the most interesting topic there is. Where did we come from? How did we get here? What brought us into existence? What is our relationship to reality as a whole?

The argument for intelligent design is based upon observation of the facts. Now that's my definition of good science. It's observation of the facts. And when you observe the facts, as Michael Behe has done, you observe this incredible pattern of interrelated complexity...

Paul Nelson

For Charles Darwin, natural selection explained the appearance of design without a designer. There was no longer any need to invoke an intelligent cause for the complexity of life. In effect, natural selection became a kind of designer substitute.

When we came together at Pajaro Dunes we certainly didn't agree on everything, but we did share a real dissatisfaction with the mechanism of natural selection and the role that it was playing in biological explanation.

The co-option argument doesn't explain this. You see, in order to construct that flagellar mechanism - or the tens of thousands of other such mechanisms in the cell - you require other machines to regulate the assembly in those structures. And those mechanisms, themselves, require machines for their assembly.

When I look at molecular machines, or the incredibly complex process by which cells divide, I want to ask, 'is it possible that these things had an intelligence behind them? That there was a plan and a purpose to this structure?'

Stephen Meyer

It's part of our knowledge base that intelligent agents can produce information-rich systems… so the argument is not based on what we don't know, but its based on what we do know about the cause and effect structure of the world.

We know, at present, there is no materialistic explanation, no natural cause that produces information. Not natural selection, not self- organizational processes, not pure chance. But we do know of a cause that is capable of producing information and that is intelligence. And so when people infer design from the presence of information in DNA, they're effectively making what's called (in the historical sciences) an inference to the best explanation.

So when we find an information-rich system in the cell, in the DNA molecule specifically, we can infer that intelligence played a role in the origin of that system, even if we weren't there to observe the system coming into existence.

Michael Behe

It's really interesting to notice that the more we know about life and the more we know about biology, the more problems Darwinism has, and the more design becomes apparent.

...for the longest time, I believed that Darwinian evolution explained what we saw in biology. Not because I saw how it could actually explain it, but because I was told that it did explain it. In schools I was taught Darwinian biology.

And through college and graduate school, I was in an atmosphere which just assumed that Darwinian evolution explained biology and, again, I didn't have any reason to doubt it.

It wasn't until about ten years ago, that I read a book called, "Evolution, a Theory in Crisis," (critique) by a geneticist by the name of Michael Denton (an Australian). And he put forward a lot of scientific arguments against Darwinian theory that I had never heard before.

...and the arguments, seemed pretty convincing. And, at that point, I started to get a bit angry because I thought I was being led down the primrose path. Here were a number of very good arguments... and I had gone through a doctoral program in biochemistry, became a faculty member... and I had never even heard of these things. And so, from that point on, I became very interested in the question of evolution and since have decided the Darwinian processes are not the whole the explanation for life.

William Dembski

I came to this trying to look at how do we reason about design. What are the logical moves that we have to go through in order to come to a conclusion of design?

And, what I am trying to to establish reliable, empirical, scientifically rigorous criteria for deciding whether something is, in fact, designed.

I was looking at the logic of it, and what I found was that you need improbability and you need specification, the right sort of pattern...

Jonathan Wells

Darwin wanted to explain everything in the history of life in terms of undesigned, unintelligent natural processes.

...and when he looked for an explanation, what he found was that a process he could observe in domestic populations also operates in the wild.

Now, Darwin, himself, was very familiar with domestic breeding. He studies pigeon breeding, and he knew that - for centuries - human breeders had been able to make dramatic changes in populations by selecting only certain individuals to breed. Darwin really suggested that this same process operates in the wild...

Scott Minnich

Howard Berg at Harvard has labeled it [the flagellar motor] the most efficient machine in the universe. These machines, some of them, are running at 100,000 rpms. And are hard-wired into a signal transduction or sensory mechanism so that it's getting feedback from the environment.

The bacterial flagellum - two gears forward and reverse, water-cooled, proton motive force. It has a stator, it has a rotor, it has a U-joint, it has a drive shaft, it has a propeller. And they function as these parts of machines...

It's not convenient that we give them these names. It's truly their function.

Irreducible complexity was coined by Mike Behe in describing these molecular machines. Basically, what it says, is that you have multicomponent parts to any organelle or system within a cell…all of which are necessary for function. That is, if you remove one part, you lose function of that system.


Previous posts include:

"Darwinism's Rules of Reasoning: Phillip Johnson on Pierre Grasse"

"Intelligent Design: 'A War on Science' (BBC Horizon Video - 49 mins)"

"Recent 'Intelligent Design The Future' Podcasts"

"Intelligent Design Defended by Unsolved Genetic Puzzle"

"Scientist Exposes Evolution's Weaknesses in Politically Incorrect Book About Darwinism and Intelligent Design"

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Tuesday, January 16, 2007


Why are lions not as big as elephants?

Carnivores are some of the widest ranging terrestrial mammals for their size, and this affects their energy intake and needs. This difference is also played out in the different hunting strategies of small and large carnivores. Smaller species less than 15-20 kg in weight specialize on very small vertebrates and invertebrates, which weigh a small fraction of their own weight, whereas larger species (greater than 15-20 kg) specialize on large vertebrate prey near their own mass.

While carnivores around the size of a lynx or larger can obtain higher net energy intake by switching to relatively large prey, the difficulty of catching and subduing these animals means that a large-prey specialist would expend twice as much energy as a small-prey specialist of equivalent body size. In a new article published by PLoS Biology, Dr. Chris Carbone and colleagues from the Institute of Zoology, Zoological Society of London reveal how this relationship might have led to the extinction of large carnivores in the past and why our largest modern mammalian carnivores are so threatened.

The authors provide a model of carnivore energetics in relation to predator and prey size, and compare the model predictions with observed estimates of metabolic rates and intake rates taken from animals in the wild. By analyzing the balance between energy intake and expenditure across a range of species, the authors reveal that mammalian carnivores would not be able to exceed a body mass of one ton.

Their model predictions are consistent with the data we have. Most mammalian carnivores are relatively small compared with the largest extinct terrestrial herbivorous mammals, such as the Indricothere, which weighed around 15 tons. The largest existing carnivore, the polar bear, is only around half a ton, while the largest known extinct carnivores, such as the short-faced bear, weighed around one ton. The authors also note that the largest terrestrial non-mammalian predators, such as Giganotosaurus and Tyrannosaurs, may have achieved their massive size by having a lower metabolic rate. Indeed, previous estimates of total metabolic rate for these species are similar to those of a mammal weighing about a ton.

We know that the largest carnivores that exist today are particularly vulnerable to threats imposed by humans and have been shown to have higher rates of extinction in the fossil record than smaller species even prior to the evolution of man. Carnivores at the upper limits of body mass would have been heavily reliant on abundant large prey to both minimize energy expenditure and maintain high rates of energy intake.

Slight environmental perturbations, anthropogenic or otherwise, leading to lower prey availability, could readily upset this energy balance. It may have also contributed to the extinction of the largest carnivores and explain why the largest modern mammalian carnivores are so rare and vulnerable today. [Source: Public Library of Science]


Based on the paper:

The Costs of Carnivory

Citation: Carbone C, Teacher A, Rowcliffe JM (2007) The Costs of Carnivory. PLoS Biol 5(2): e22 doi:10.1371/journal.pbio.0050022


Predators face severe energetic constraints that affect many aspects of their ecology and evolution. Many species in the Order Carnivora, for example, are at a high trophic level, with their population biomass representing only a small fraction of that of their prey. The largest prey species themselves, can be unpredictable in space and time, widely dispersed, and rare. Consequently, carnivores are some of the widest ranging terrestrial mammals for their size, and this affects overall energy budgets.

Carnivores also exhibit different hunting strategies in relation to their mass. Smaller species (less than 15-20 kg) specialize in very small vertebrates and invertebrates which weigh a small fraction of their own weight. The larger species (greater than 15-20 kg), on the other hand, specialize in large-vertebrate prey near their own mass. Small-prey-feeding carnivores appear to have relatively low hunting costs - searching and pursuit can occur at walking pace and the capture and killing phases are often very brief. Large carnivores, however, with their large prey, have higher hunting costs, with long high-speed chases and high costs of capture and killing.

Thus far, however, there has been no general framework to interpret adjustments in carnivore energy budgets associated with changes in body mass and hunting strategy. In this paper, we develop a simple model to examine adjustments in carnivore energetics in relation to predator and prey size and compare the model predictions with observed estimates of field metabolic rates (FMR) and intake rates. Our approach provides a framework to understand adjustments in carnivore energy budgets and provides insights into the evolution of body size in this diverse group.


A post from a different perspective (Friday, August 04, 2006): "What determines body size?"

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