Stability and Responsiveness in a Self-Organized Living Architecture
Publication Date
March 28, 2013
Journal
PLOS Computational Biology
Authors
Simon Garnier, Tucker Murphy, Matthew Lutz, Edward Hurme, et al
Volume
9
Issue
3
Pages
e1002984
DOI
https://dx.plos.org/10.1371/journal.pcbi.1002984
Publisher URL
http://journals.plos.org/ploscompbiol/article?id=10.1371%2Fjournal.pcbi.1002984
PubMed
http://www.ncbi.nlm.nih.gov/pubmed/23555219
PubMed Central
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3610604
Europe PMC
http://europepmc.org/abstract/MED/23555219
Web of Science
000316864200054
Scopus
84876002467
Mendeley
http://www.mendeley.com/research/stability-responsiveness-selforganized-living-architecture
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Mendeley | Further Information

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Scopus | Further Information

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Figshare

  • {"files"=>["https://ndownloader.figshare.com/files/1000847", "https://ndownloader.figshare.com/files/1000848", "https://ndownloader.figshare.com/files/1000849", "https://ndownloader.figshare.com/files/1000850", "https://ndownloader.figshare.com/files/1000852"], "description"=>"<div><p>Robustness and adaptability are central to the functioning of biological systems, from gene networks to animal societies. Yet the mechanisms by which living organisms achieve both stability to perturbations and sensitivity to input are poorly understood. Here, we present an integrated study of a living architecture in which army ants interconnect their bodies to span gaps. We demonstrate that these self-assembled bridges are a highly effective means of maintaining traffic flow over unpredictable terrain. The individual-level rules responsible depend only on locally-estimated traffic intensity and the number of neighbours to which ants are attached within the structure. We employ a parameterized computational model to reveal that bridges are tuned to be maximally stable in the face of regular, periodic fluctuations in traffic. However analysis of the model also suggests that interactions among ants give rise to feedback processes that result in bridges being highly responsive to sudden interruptions in traffic. Subsequent field experiments confirm this prediction and thus the dual nature of stability and flexibility in living bridges. Our study demonstrates the importance of robust and adaptive modular architecture to efficient traffic organisation and reveals general principles regarding the regulation of form in biological self-assemblies.</p> </div>", "links"=>[], "tags"=>["responsiveness", "self-organized"], "article_id"=>662368, "categories"=>["Neuroscience"], "users"=>["Simon Garnier", "Tucker Murphy", "Matthew Lutz", "Edward Hurme", "Simon Leblanc", "Iain D. Couzin"], "doi"=>["https://dx.doi.org/10.1371/journal.pcbi.1002984.s001", "https://dx.doi.org/10.1371/journal.pcbi.1002984.s002", "https://dx.doi.org/10.1371/journal.pcbi.1002984.s003", "https://dx.doi.org/10.1371/journal.pcbi.1002984.s004", "https://dx.doi.org/10.1371/journal.pcbi.1002984.s005"], "stats"=>{"downloads"=>4, "page_views"=>31, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Stability_and_Responsiveness_in_a_Self_Organized_Living_Architecture_/662368", "title"=>"Stability and Responsiveness in a Self-Organized Living Architecture", "pos_in_sequence"=>0, "defined_type"=>4, "published_date"=>"2013-03-29 13:17:28"}
  • {"files"=>["https://ndownloader.figshare.com/files/1000839"], "description"=>"<p>(a) Drawing representing a living bridge formed by the army ant <b><i>Eciton burchellii</i></b> between two leaves (by TM). The black bar illustrate how we measured the gap size as the maximum distance spanned by the ants. (b) Temporal dynamics of the traffic over the gap (in ants/10 second period) and (c) of the number of ants participating in the bridge structure (in ants/10 second period) as a function of time, before (negative times) and after (positive times) the removal of the bridge. For each time period, the cross (+) represents the median value for 39 data points; the box represents the 2nd and 3rd quartiles of the value distribution; the whiskers represent the 1st and 4th quartiles; the circles (o) represent outliers. The solid black line shows an estimation of the evolution of each value by a GLMM, with its 95% confidence interval (dotted lines).</p>", "links"=>[], "tags"=>["neuroscience"], "article_id"=>662360, "categories"=>["Neuroscience"], "users"=>["Simon Garnier", "Tucker Murphy", "Matthew Lutz", "Edward Hurme", "Simon Leblanc", "Iain D. Couzin"], "doi"=>"https://dx.doi.org/10.1371/journal.pcbi.1002984.g001", "stats"=>{"downloads"=>3, "page_views"=>21, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Figure_1_/662360", "title"=>"Figure 1", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2013-03-29 13:14:26"}
  • {"files"=>["https://ndownloader.figshare.com/files/1000840"], "description"=>"<p>(a) Survival analysis of the time spent by ants as part of the bridge structure during the 2 minutes after the destruction of the bridge. A CPHM reveals that this time decreases with the size (or caste) of the ant as shown here, and increases with the overall packing density of ants on the bridge (number of ants by unit length of the bridge). It also shows that ants joining the bridge earlier are less likely to leave it. (b) Distribution of the different castes across three different dynamic structures (bridge - n = 920 -, bivouac - n = 573 - and raid - n = 3314). The proportion of minor in the bridge is similar to the one found in bivouac, but different from the one found in the raiding trail. The inverse tendency can be observed for media ants. Data for bivouacs and raiding trails from <a href=\"http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1002984#pcbi.1002984-Franks1\" target=\"_blank\">[25]</a>.</p>", "links"=>[], "tags"=>["differences", "castes"], "article_id"=>662361, "categories"=>["Neuroscience"], "users"=>["Simon Garnier", "Tucker Murphy", "Matthew Lutz", "Edward Hurme", "Simon Leblanc", "Iain D. Couzin"], "doi"=>"https://dx.doi.org/10.1371/journal.pcbi.1002984.g002", "stats"=>{"downloads"=>1, "page_views"=>21, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Behavioural_differences_between_castes_related_to_bridge_construction_/662361", "title"=>"Behavioural differences between castes related to bridge construction.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2013-03-29 13:14:50"}
  • {"files"=>["https://ndownloader.figshare.com/files/1000841"], "description"=>"<p>(a) The time spent in the bridge by an ant <b><i>i</i></b> increases as a function of the traffic flow over this individual (GLMM, p<0.0001). This data is best modeled by an exponential increase of the form , with <b><i>ρ</i></b> = 1.959, <b><i>σ</i></b> = 2.789, and represents the traffic over the individual. (b) The time spent in the bridge by an ant increases as a function of the number of surrounding ants in the structure (GLMM, p = 0.016).</p>", "links"=>[], "tags"=>["behavioural", "subset", "50"], "article_id"=>662362, "categories"=>["Neuroscience"], "users"=>["Simon Garnier", "Tucker Murphy", "Matthew Lutz", "Edward Hurme", "Simon Leblanc", "Iain D. Couzin"], "doi"=>"https://dx.doi.org/10.1371/journal.pcbi.1002984.g003", "stats"=>{"downloads"=>0, "page_views"=>28, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Detailed_behavioural_analysis_of_a_subset_of_50_ants_/662362", "title"=>"Detailed behavioural analysis of a subset of 50 ants.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2013-03-29 13:14:55"}
  • {"files"=>["https://ndownloader.figshare.com/files/1000842"], "description"=>"<p>(a) Example of the typical variation in traffic intensity on a foraging trail. Data obtained from the Particle Image Velocimetry algorithm are shown in grey. The black line is obtained by computing a running average on the data with a window of ½ second. (b) Distribution of the dominant frequencies of traffic oscillations on 57 foraging trails. The black circles at the bottom of the figure represent the actual observed frequencies. The grey bars and the continuous black line represent the estimated distribution of these observed densities in the form of a histogram and of a density plot, respectively. The dashed black line represents the median value of the distribution (0.293 Hz, which corresponds to a median period of 3.413 seconds).</p>", "links"=>[], "tags"=>["neuroscience"], "article_id"=>662363, "categories"=>["Neuroscience"], "users"=>["Simon Garnier", "Tucker Murphy", "Matthew Lutz", "Edward Hurme", "Simon Leblanc", "Iain D. Couzin"], "doi"=>"https://dx.doi.org/10.1371/journal.pcbi.1002984.g004", "stats"=>{"downloads"=>1, "page_views"=>7, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Figure_4_/662363", "title"=>"Figure 4", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2013-03-29 13:15:10"}
  • {"files"=>["https://ndownloader.figshare.com/files/1000843"], "description"=>"<p>(a) Resistance of the bridge to traffic variations. The values represents the non-empty bridge time ratio (<b><i>i.e.,</i></b> at least one ant stopped in the gap) as a function of the oscillation period and the oscillation intensity of the traffic on the trail in simulations of the model (simulation length: 100 oscillation periods). The horizontal dashed line represents the typical dominant oscillation period as observed on natural trails of army ants (see <a href=\"http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1002984#pcbi-1002984-g003\" target=\"_blank\">Figure 3b</a>). Inset is the non-empty bridge time ratio as a function of the mean traffic flow on the trail in simulations of the model. (b) Bridge reactivity to sudden interruption of the traffic. The solid line represents the mean correlation (the shaded region being the +/−95% confidence interval) between the traffic on the trail (measured by blocks of 10 seconds) and the number of ants bridging the gap during 10 experiments where the traffic was interrupted by sweeping ants off the trail, at different time lags (0 to 100 seconds by 10 seconds intervals). The dashed line represents the same measurement for 10,000 simulations with the same starting conditions (gap size and number of ants bridging the gap when trail sweeping started) and the same traffic conditions as in the experiments.</p>", "links"=>[], "tags"=>["neuroscience"], "article_id"=>662364, "categories"=>["Neuroscience"], "users"=>["Simon Garnier", "Tucker Murphy", "Matthew Lutz", "Edward Hurme", "Simon Leblanc", "Iain D. Couzin"], "doi"=>"https://dx.doi.org/10.1371/journal.pcbi.1002984.g005", "stats"=>{"downloads"=>1, "page_views"=>25, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Bridge_sensitivity_to_traffic_conditions_/662364", "title"=>"Bridge sensitivity to traffic conditions.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2013-03-29 13:15:25"}
  • {"files"=>["https://ndownloader.figshare.com/files/1000844"], "description"=>"<p>Light grey stars represent the experimental data; upper stars represent ants that decided to join the bridge structure; lower stars represent ants that crossed the gap without stopping. The grey surface represent the best fit of a 3 dimensional sigmoidal function to the experimental data.</p>", "links"=>[], "tags"=>["ant", "decides", "packing", "instantaneous"], "article_id"=>662365, "categories"=>["Neuroscience"], "users"=>["Simon Garnier", "Tucker Murphy", "Matthew Lutz", "Edward Hurme", "Simon Leblanc", "Iain D. Couzin"], "doi"=>"https://dx.doi.org/10.1371/journal.pcbi.1002984.g006", "stats"=>{"downloads"=>4, "page_views"=>22, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Probability_that_an_ant_passing_over_the_gap_decides_to_participate_in_bridge_construction_as_a_function_of_the_packing_density_of_the_bridge_and_the_instantaneous_traffic_on_the_trail_/662365", "title"=>"Probability that an ant passing over the gap decides to participate in bridge construction as a function of the packing density of the bridge and the instantaneous traffic on the trail.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2013-03-29 13:15:32"}

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Relative Metric

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