patches-own [ cur-state ;; patch will cooperate new-state ;; patch next state dom-species ] to setup clear-all ask patches [ ifelse (random-float 1.0 < 0.1) [set cur-state 0 ] [ set cur-state random number-of-species + 1 ] establish-color ] reset-ticks end to go ask patches [interact] ;; to play with a neighboring patch ask patches [adopt-strategy] ;; adopt the strategy of the neighbor (who had the highest score) tick end to go-once ask patches [interact] ;; to play with a neighboring patch ask patches [adopt-strategy] ;; adopt the strategy of the neighbor (who had the highest score) tick end to interact ;; patch procedure set new-state cur-state let ran-neigh one-of neighbors ifelse new-state = 0 [ set new-state [cur-state] of ran-neigh ] ;; growth - probability equal for all species [ set dom-species cur-state - 1 if dom-species = 0 [ set dom-species number-of-species ] if [cur-state] of ran-neigh = dom-species [ ifelse dom-species = 1 [ if random-float 1.0 < 0.5 * comp-factor-species-1 [ ifelse direct-overgrowth [set new-state dom-species] [set new-state 0] ] ] [ if random-float 1.0 < 0.5 [ ifelse direct-overgrowth [set new-state dom-species] [set new-state 0] ] ] ] if random-float 1.0 < 0.05 ;; background death rate [set new-state 0] ] end to adopt-strategy ;; patch procedure set cur-state new-state establish-color end to establish-color ;; patch procedure if cur-state = 0 [set pcolor black ] if cur-state = 1 [set pcolor red ] if cur-state = 2 [set pcolor yellow] if cur-state = 3 [set pcolor green] if cur-state = 4 [set pcolor cyan] if cur-state = 5 [set pcolor blue ] if cur-state = 6 [set pcolor magenta ] if cur-state = 7 [set pcolor pink ] end ; Copyright 2002 Uri Wilensky. Adapted by M.C. Boerlijst 2022 ; See Info tab for full copyright and license. @#$#@#$#@ GRAPHICS-WINDOW 416 26 817 428 -1 -1 3.0 1 10 1 1 1 0 1 1 1 -65 65 -65 65 1 1 0 ticks 20.0 BUTTON 11 42 123 75 random start setup NIL 1 T OBSERVER NIL NIL NIL NIL 1 BUTTON 11 81 88 114 NIL go T 1 T OBSERVER NIL NIL NIL NIL 0 BUTTON 11 120 107 153 1 timestep go-once NIL 1 T OBSERVER NIL NIL NIL NIL 1 MONITOR 9 161 138 206 fraction Empty count patches with\n [ pcolor = black ]\n/ count patches 3 1 11 PLOT 10 218 395 431 Populations ticks fraction 0.0 5.0 0.0 0.01 true true "" "" PENS "1" 1.0 0 -2674135 true "" "plot (count patches with [pcolor = red] / count patches)" "2" 1.0 0 -1184463 true "" "plot (count patches with [pcolor = yellow] / count patches)" "3" 1.0 0 -14439633 true "" "plot (count patches with [pcolor = green ] / count patches)" "4" 1.0 0 -11221820 true "" "plot (count patches with [pcolor = cyan] / count patches)" "5" 1.0 0 -14070903 true "" "plot (count patches with [pcolor = blue] / count patches)" "6" 1.0 0 -7858858 true "" "plot (count patches with [pcolor = magenta] / count patches)" "7" 1.0 0 -4757638 true "" "plot (count patches with [pcolor = pink] / count patches)" SLIDER 166 100 348 133 comp-factor-species-1 comp-factor-species-1 0.5 2 1.0 0.02 1 NIL HORIZONTAL CHOOSER 167 42 289 87 number-of-species number-of-species 2 3 4 5 6 7 1 SWITCH 167 148 338 181 direct-overgrowth direct-overgrowth 1 1 -1000 @#$#@#$#@ ## WHAT IS IT? This is a model to study the effect of spatial pattern formation on dynamics of cyclic competition between species. Such "intransitive loops" are for instance observed in competitive dominance between coral species (see Johson & Seinen, 2002). The model is taken from Boerlijst & Hogeweg, 1995, who studied "hypercycles with negative interactions". ## HOW TO USE IT The model can be started with "random start", which seeds the field with 90% coverage with equal numbers of each species. During each tick, all patches are updated. During an update empty patches can obtain an offspring from a randomly chosen neighbor patch, and occupied patches can die due to a dominant species in a neighbor patch. ## HOW IT WORKS In the model a variable number of species can be simulated, who form one large cycle of competitive dominance, where species 1 > 2 > 3 > ... > n > 1. Every time step each patch chooses a random neighbor (out of the 8 direct neighbors). If the patch is empty it produces an offspring of the species in the neighbor patch. If the patch is full, it determines whether the neighbor contains the dominant species. If this is the case the patch becomes empty with high probability (50%). Note that there is also a 5% change of background mortality in the absence of dominance. ## THINGS TO NOTICE Start with a system with 3 species. Notice that the cyclic dominance is reflected in a spatial pattern formation that quickly is established, and where each species sits directly behind the species that it dominates. Note that this description only applies to a system of 3 species. For other number of species other patterns emerge, which can be found via "things to try". ## THINGS TO TRY Change the number of species and restart the field. First study the pattern with 2 species, and than try to understand what happens if the system consists of 4 species. If this is clear, you can go to a system of 5 species. Here, you have to carefully study the spatial succession of the species (i,.c. which species is locally overtaking the previous dominant species?). Can you understand this order of succession? Now study what happens if you vary the relative dominance of species 1 over species 2. This can be done by adjusting the slider "comp-factor-species-1". First try this in a system with 3 species. What would you expect if species 1 becomes more aggressive towards species 2? Check your prediction (set comp-factor-species-1 to 1.5) and try to explain! Check what happens to the dynamics of the system if the dominant species can directly overgrow the patch of the other species. This can be done by setting the switch "direct-overgrowth". How does this affect the 3 species system? How does this direct overgrow affect the dynamics for systems with other number of species? Note that with the direct overgrowth the system resembles the spatial Hypercycle dynamics. I have also uploaded a Netlogo model for that system. ## REFERENCES Boerlijst, M.C.; Hogeweg, P. , Attractors and Spatial Patterns in Hypercycles with Negative Interactions (1995) Journal of theoretical Biology, volume 176, pp. 199 - 210. https://doi.org/10.1006/jtbi.1995.0191 Johnson, C.R., Seinen, I., 2002. Selection for restraint in competitive ability in spatial competition systems. Proc. R. Soc. London B 269, 655–663. https://doi.org/10.1098/rspb.2001.1948 Please cite the NetLogo software as: * Wilensky, U. (1999). NetLogo. http://ccl.northwestern.edu/netlogo/. Center for Connected Learning and Computer-Based Modeling, Northwestern University, Evanston, IL. ## COPYRIGHT AND LICENSE The model was adapted from the basic Prisoners Dilemma model from the Netlogo Models Library (Copyright 2002 Uri Wilensky). Code adapted by M.C. 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