JBI_buffer_effectiveness
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SUPPORTING INFORMATION, APPENDIX 1 OOD OVERVIEW Purpose and patterns. The degree to which alpine vegetation is globally and locally threatened by climate change centers on the existence and functioning of microrefugia. Our purpose is to determine how the degree of climatic buffer effectiveness affects the potential conservation versus loss of species from a virtual microcosm designed to represent and alpine slope. The simulation was created in Netlogo. Heterogeneity in climate was the basic environmental pattern. Patches of microrefugia were superimposed on the basic pattern. Processes of new establishment and mortality were implemented with Monte Carlo stochasticity. We ran the simulation model in an experimental mode. These simulation experiments used all combinations of 11 levels of area and 3 levels of initial pattern complexity of the environment. The experimental designs were run independently, and their results are compared. The simulation experiments plus two special cases are outlined below. Entities, state variables, and scales. The model represents a mountain slope as a virtual microcosm and so scale is not considered precisely because the simulation experiments address relative effects of the parameters. Each cell of habitat has a value for an environmental gradient that is initialized in one of three spatial patterns. The plant communities of these alpine habitats are represented by 100 individual virtual species, the agents, each differently adapted to the environmental gradient in even increments so that they had the potential to fill all niches and occupy all locations. Process overview and scheduling. Within each simulation, at each iteration agents reproduce, and the offspring disperse across the grid; agents are removed randomly to maintain a maximum density; and agents are removed depending on their adaptation to the grid cell climate or location. The diversity of the areas of habitat are calculated at the end of all iterations (following equilibrium). The simulations appear to equilibrate immediately (no change through 50 iterations) but become complicated during periods of climate change (50-150 years) after which most cases equilibrated within another 3 years. The simulations were replicated 10 times using the same 10 random number seeds for all combinations. DESIGN CONCEPTS The simulations quantify the effects of degrees of buffer effectiveness in the context of differing initial complexity of the pattern of climates The agents are not goal-oriented; behavior is random; the agents sense the environment of the grid cell they occupy and their fitness relative to it determines probabilities of reproduction and death. Agents compete indirectly for space via random deletion of agents when cell density is greater than a set value. The central processes are Monte Carlo reproduction and mortality so that the species are selected by the environment of the grid cells (i.e., fitness). The plant diversity of the alpine region, represented by the presence of species on all its grid cells, is the object of analysis. The diversity for the simulated area is the sole output of the simulation. The agents do not adapt, learn, or predict, nor is there emergent behavior. DETAILS Initialization Landscape. The environment of each cell of the grid was initialized in a fractal pattern (hills) with microrefugia superimposed on it (Figure A1.1). A topography subroutine in NetLogo is used. It assigns peaks to random cells and successively divides the height of all cells to its neighbors. Three such levels of initial pattern complexity are used. X peaks are randomly chosen from among the 10000 cells. Each peak is assigned an elevation of 1000. 100% of this elevation is diffused to the 8 neighboring cells. This diffusion is repeated Y times, with the new topography being diffused at each step. The parameter values are (Table A1.1): Table A1.1: Parameter values for initial landscape patterns Pattern Peaks Diffusions 1 1000 100 2 2000 25 3 1000 5
The resulting elevation values of the cells are then normalized to the range 0-1 taking the value minus the grid minimum and dividing by the range. Because the result is skewed left from a normal distribution with a mean of 0,5, the square root was calculated. Next, microrefugia patches were superimposed on the grid. The patches were regularly and evenly distributed. For example, for 25 patches every 20th row and column were chosen as the patch center. An area around this cell was defined as a microrefugia patch by taking a radius in number of cells that would sum as close to 1500 as possible. The position on the climate gradient of these cells was taken as a random number in the range 0.0-0.3. If the number of microrefugia cells was less than or greater than 1500, cells on the edge of the patch were reassigned to 0.0-0.3 or 0.3-0.4, respectively. To maintain symmetry in the range of climate gradient values, cells in the 0.7 to 1.0 or 0.3-0.7 ranges were reassigned randomly to the range 0.3 to 0.7 to reach 1500 cells in the upper 30%. Each grid was wrapped into a torus to eliminate edge effects.
Figure A1.1. Examples of the three levels of complexity, increasing A-C, in the initial landscape patterns of the climate gradient. Microrefugia are superimposed on the initial pattern. The 0-1 climate gradient is represented by a heat map of dark to light shades. the former are the microrefugia, the latter are the highest temperatures; i.e., the microrefugia are the darkest areas (0-0.3) that look like added balls, and are superimposed on patterns of higher temperatures (0.3-1The superimposed patches cover the range 0.0-0.3, and the rest of the slope has the range 0.3-1.0
Virtual species 100 virtual species were defined in the simulation. Each species has a Gaussian response function over the climatic gradient as illustrated by Figure A1S2.
Figure A1.2. 100 virtual species (not all shown) have response or fitness functions evenly distributed on the climatic gradient with modes spaced from 0.01 to 1.0 in increments of 0.01. The response of species i at position x on the environmental gradient is: Rix=e^(-〖(((E〗x 〖-m_i)〗^2 〖/2σ〗^2))))
where Ex is the position of the cell on the environmental gradient; the mi is the position of the mode of the species on the gradient; and σ2 is the standard deviation of the Gaussian function, chosen here as 0.0005, which produced distributions of regional species richness (2-100) spanning nearly the full possible range across all simulations. The outcomes have minor sensitivity to a difference in the standard deviation of one order of magnitude. Thus, 100 such equations define 100 virtual species. The response variable Rix was calculated for every species and every cell using this code: Set Rix exp ( ( (( CGVx - (i/100)) ^ 2 ) / 0.001 ) * -.5) Where CGVx is the climate value of the cell x and i/100 is the position of the mode of the ith species on the gradient. This approach follows earlier theoretical models of species distributions on environmental gradients (e.g., Gauch and Whittaker 1976), but we recognize that Gaussian functions are not necessarily common (Falster et al. 2021). This extreme simplification was selected following Malanson et al. (2023) who had evaluated it against three alternatives. For its climate, each cell on the grid is then assigned a response value for each of 100 virtual species. The initial distribution of species on the grid cells was simulated by comparing Rix for the 100 virtual species on the 10000 cells to a random number in the range 0.0-1.0. If Rix was the higher, an individual with a random age of 50-150 years was created (seedlings were not included because most die immediately but at a computational cost). Then random individuals from all species were removed one by one until so that the total number equaled 10; these are cover units based on the number of individuals, which is not spatial-scale specific given the variability if the size and shape of alpine plants. This limit was the basis for calculating CPE, expanded below, and chosen to limit computational burden). This procedure was repeated 5 times.
Submodels The models cycle through five submodels or procedures. One, climate change, is used only during years 50-150, and is an exogenous driver. The others, competition, establishment, rescue effect, and mortality (there are separate mortality subroutines for seedlings and established plants), are species demographic calculations and are executed at every iteration. The simulations extended to 200 iterations. Environmental gradients Climate change. Climate change is based on the pattern or change illustrated by Scherrer and Korner 2010, 2011 for a 2 K warming but extended to 5 K warming (e.g., Coppola at al. 2021). During the period of climate change, in iterations 50-150, 0.005 was added to the climate gradient value of every cell except the microrefugia cells. For the microrefugia, the addition was in the range of 0.005 to 0.0, descending in even steps (0.005, 0.0045, 0.004,…, 0.0) to represent 11 levels of buffer effectiveness from 0% (the change is the same as on the rest of the cells) to 100% (the GCV of the microrefugia cells never change). The differences in buffer effectiveness are applied to all microrefugia cells in different simulation runs. For an additional comparison we added a special case in which we divided the grid into quarters and assigned buffering effectiveness of 100%, 75%, 50% and a random value of 0-100% to the to the refugia cells of those quarters, respectively. We ran this version only for the 25 microrefugia patch treatment but with all three initial pattern complexities. Demographic calculations A model of this nature is not able to precisely model the absolute values of populations or infer specific rates of survival or extinction. Instead, for experimental treatments it is necessary to assess whether the results are significantly different in terms of their means and variance. To avoid creating outcomes that are wholly the artifacts of model inputs, we parameterize the relative levels of the Monte Carlo probabilities using the related observed levels for 150 alpine species used in a mechanistic simulation by Dullinger et al. (2012). Competition. Dullinger et al. (2012) implemented a density dependent function that affected demographic processes. They used species-specific dependence, but we used an area-based carrying capacity of 10 cover units based on the number of individuals, which is not spatial-scale specific given the variability if the size and shape of alpine plants, and we calculated two multipliers to differentiate the effects of extant competitors on seedlings and older plants. For each cell a multiplier is set at J = 1 - 0.1 * C where C is the number of individuals on the cell, was applied to the Rix of all species. JRix was applied to the probability of establishment and to the probability of mortality in the subsequent two years. A different multiplier, K = 1 – 0.02 * C was used for KRix and applied to the probability of mortality individuals of age > 2. JRix and KRix are recalculated for every species on every cell at every iteration.
Dispersal and Establishment. On each cell that did not already have 10 individuals, a new individual of a species was created if one of that species was within dispersal range. Half of the species were designated as ubiquitous dispersers, while the other half had limited dispersal (along the climate gradient, the dispersal type alternated so that the environmental associations and dispersal abilities were completely mixed). Ubiquitous dispersers, if extant anywhere on the grid, added a potential new individual to every cell that did not already have 10 individuals in every year. Although this approach appears to copy the unlimited dispersal treatments included by Dullinger et al., because of the smaller area it is within the tails of the hybrid distributions of that model and is realistic. Limited dispersers added potential offspring to cells with less than 10 individuals gained a potential offspring of limited dispersal species if one was within a radius of 3.2 cells, which encompasses the nearest 36 neighbors and the cell in question. Sensitivity analyses with the nearest 13 and 57 neighbors show no differences (Supporting Information, Appendix 2, Preliminary Analyses, Figure A2.2) An additional source of new offspring was simulated. A single individual of each ubiquitous dispersing species, whether extant on the grid or not, was added to a random cell among the 10,000 to represent the very low probability but sometimes observed long distance rescue effect. Mortality. This seed rain would be extraordinarily high if it resulted in establishment, but the mortality subroutine for new individuals is used immediately and the individual is eliminated if its priority-reduced JRix is less than a random number in the range zero to the parameter value shown in Table A1.2 (the difference is based on the assumption that limited dispersal is associated with higher survivorship on an r-K continuum). The parameter values were chosen based on a the ratio of high and low juvenile mortality among the rates of the 150 species used by Dullinger et al. (2012)(their median value was 0.7, and we use a values of 0.2:0.3). Older individuals died using the same process but with KRix. The values for older individuals were initially the same as for new establishment, and then the higher mortality for the ubiquitous dispersers was increased until the number of species in the simulation during the initial equilibrium period dropped below 100. Our rationale is that this mortality rate should be as high as possible to counter the high seed rain, but the 100 species of pre-climate change period should all be present. Lastly, random individuals were removed if the number on a cell was greater than 10 to maintain carrying capacity. We ran additional simulations as sensitivity tests. Having used a proportional approach to derive the values in Table A1.2, we increased and decreased the difference between the dispersal types. The bimodal response in #VS to buffer effectiveness was repeated and even more pronounced in both. The specific results are shown in Supporting Information, Appendix 2, Preliminary Analyses. Table A1.2 The values used to determine mortality or survival of individuals at every iteration. The probability of mortality is higher for new seedlings and for species with ubiquitous dispersal. Age (years) Dispersal 0-2 >2 Limited 0.3 0.2 Ubiquitous 0.8 0.2
Simulation experiments The experiments consist of the inclusion of buffer effectiveness and competitive priority effects with different spatial patterns and two special cases (Table A1.3). The focal simulations have 3 patterns, 11 levels of buffer effectiveness, and priority effects (33 simulations, 3 replications each). To these runs are added an additional 99 by removing priority effects. The two special cases are simulations with 25 buffer levels used simultaneously in the 25 different microrefugia and an equilibrium calculation for climate change as a single, instantaneous event without the calculation of the transient demographic processes The 25 simultaneous buffer and equilibrium simulations use the three patterns and three replications for nine runs each.
Table A1.3. The combinations of processes included or excluded from simulation runs that constituted the experiments. Process Values Initial pattern 3 patterns Buffer effectiveness 11 (0-100%) + all* Priority effects YES, NO Equilibrium NO, YES† * the full range of effectiveness is allotted across all microrefugia as 25 unique levels. The full range of 0% effectiveness (0.005) is divided into 25 increments and one of these values (0.0002, 0.0004, …, 0.005) is added to each cell of a microrefugia, chosen randomly at the initialization, in each year of climate change; competitive priority effects are included for three replications of the three levels of initial pattern. † in the equilibrium simulations, no processes and so no competitive priority effects, are included. Three levels of the initial pattern and 11 levels of buffer effectiveness are included and replicated three times.
Output The number of virtual species and the number of individuals of each species across the grid at the end of the simulation run, year 200, were summed from their presences on each cell. Selected examples of the latter are presented in the main text
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globals [ ;THE FOLLOWING DECLARES GLOBAL VARIABLES, FOLLOWED BY THE 100 VIRTUAL SPECIES, AND ; THEN BY THE VARIABLES THAT ARE AGENT AND PATCH SPECIFIC ; IN NETLOGO EACH CELL IS A "PATCH" minergy maxergy renergy axaxis counterr counterdie10 counter1 counter2 counter3 counterN counterP counterQ counterC direct grad limit mean1 mean2 median1 median2 std1 std2 max1 max2 min1 min2 maxC2 minC2 renC2 Si Sj BCij smooth gamma climbase mclim addclim adm agedi xrand yrand randyr Connect1 Connect2 year mq1 mq2 cq1 cq2 extracount extracountA extracountB dispB radi peaks seed ] breed [Sp1s Sp1] breed [Sp2s Sp2] breed [Sp3s Sp3] breed [Sp4s Sp4] breed [Sp5s Sp5] breed [Sp6s Sp6] breed [Sp7s Sp7] breed [Sp8s Sp8] breed [Sp9s Sp9] breed [Sp10s Sp10] breed [Sp11s Sp11] breed [sp12s Sp12] breed [Sp13s Sp13] breed [Sp14s Sp14] breed [Sp15s Sp15] breed [Sp16s Sp16] breed [Sp17s Sp17] breed [Sp18s Sp18] breed [Sp19s Sp19] breed [Sp20s Sp20] breed [Sp21s Sp21] breed [Sp22s Sp22] breed [Sp23s Sp23] breed [Sp24s Sp24] breed [Sp25s Sp25] breed [Sp26s Sp26] breed [Sp27s Sp27] breed [Sp28s Sp28] breed [Sp29s Sp29] breed [Sp30s Sp30] breed [Sp31s Sp31] breed [Sp32s Sp32] breed [Sp33s Sp33] breed [Sp34s Sp34] breed [Sp35s Sp35] breed [Sp36s Sp36] breed [Sp37s Sp37] breed [Sp38s Sp38] breed [Sp39s Sp39] breed [Sp40s Sp40] breed [Sp41s Sp41] breed [Sp42s Sp42] breed [Sp43s Sp43] breed [Sp44s Sp44] breed [Sp45s Sp45] breed [Sp46s Sp46] breed [Sp47s Sp47] breed [Sp48s Sp48] breed [Sp49s Sp49] breed [Sp50s Sp50] breed [Sp51s Sp51] breed [Sp52s Sp52] breed [Sp53s Sp53] breed [Sp54s Sp54] breed [Sp55s Sp55] breed [Sp56s Sp56] breed [Sp57s Sp57] breed [Sp58s Sp58] breed [Sp59s Sp59] breed [Sp60s Sp60] breed [Sp61s Sp61] breed [Sp62s Sp62] breed [Sp63s Sp63] breed [Sp64s Sp64] breed [Sp65s Sp65] breed [Sp66s Sp66] breed [Sp67s Sp67] breed [Sp68s Sp68] breed [Sp69s Sp69] breed [Sp70s Sp70] breed [Sp71s Sp71] breed [Sp72s Sp72] breed [Sp73s Sp73] breed [Sp74s Sp74] breed [Sp75s Sp75] breed [Sp76s Sp76] breed [Sp77s Sp77] breed [Sp78s Sp78] breed [Sp79s Sp79] breed [Sp80s Sp80] breed [Sp81s Sp81] breed [Sp82s Sp82] breed [Sp83s Sp83] breed [Sp84s Sp84] breed [Sp85s Sp85] breed [Sp86s Sp86] breed [Sp87s Sp87] breed [Sp88s Sp88] breed [Sp89s Sp89] breed [Sp90s Sp90] breed [Sp91s Sp91] breed [Sp92s Sp92] breed [Sp93s Sp93] breed [Sp94s Sp94] breed [Sp95s Sp95] breed [Sp96s Sp96] breed [Sp97s Sp97] breed [Sp98s Sp98] breed [Sp99s Sp99] breed [Sp100s Sp100] turtles-own [ age dista3 dista4 deathv] patches-own [ refuge room roomA roomD roomR SorsN1 SorsT1 SorsS1 climate1 climate2 climate3 climate4 ASq1 ASq2 ASq3 Asq4 ASq5 ASq6 ASq7 ASq8 ASq9 ASq10 ASq11 ASq12 ASq13 ASq14 ASq15 ASq16 ASq17 ASq18 ASq19 ASq20 ASq21 ASq22 ASq23 ASq24 ASq25 ASq26 ASq27 ASq28 ASq29 ASq30 ASq31 ASq32 ASq33 ASq34 ASq35 ASq36 ASq37 ASq38 ASq39 ASq40 ASq41 ASq42 ASq43 ASq44 ASq45 ASq46 ASq47 ASq48 ASq49 ASq50 ASq51 ASq52 ASq53 ASq54 ASq55 ASq56 ASq57 ASq58 ASq59 ASq60 ASq61 ASq62 ASq63 ASq64 ASq65 ASq66 ASq67 ASq68 ASq69 ASq70 ASq71 ASq72 ASq73 ASq74 ASq75 ASq76 ASq77 ASq78 ASq79 ASq80 ASq81 ASq82 ASq83 ASq84 ASq85 ASq86 ASq87 ASq88 ASq89 ASq90 ASq91 ASq92 ASq93 ASq94 ASq95 ASq96 ASq97 ASq98 ASq99 ASq100 ASQR1 ASQR2 ASQR3 ASQR4 ASQR5 ASQR6 ASQR7 ASQR8 ASQR9 ASQR10 ASQR11 ASQR12 ASQR13 ASQR14 ASQR15 ASQR16 ASQR17 ASQR18 ASQR19 ASQR20 ASQR21 ASQR22 ASQR23 ASQR24 ASQR25 ASQR26 ASQR27 ASQR28 ASQR29 ASQR30 ASQR31 ASQR32 ASQR33 ASQR34 ASQR35 ASQR36 ASQR37 ASQR38 ASQR39 ASQR40 ASQR41 ASQR42 ASQR43 ASQR44 ASQR45 ASQR46 ASQR47 ASQR48 ASQR49 ASQR50 ASQR51 ASQR52 ASQR53 ASQR54 ASQR55 ASQR56 ASQR57 ASQR58 ASQR59 ASQR60 ASQR61 ASQR62 ASQR63 ASQR64 ASQR65 ASQR66 ASQR67 ASQR68 ASQR69 ASQR70 ASQR71 ASQR72 ASQR73 ASQR74 ASQR75 ASQR76 ASQR77 ASQR78 ASQR79 ASQR80 ASQR81 ASQR82 ASQR83 ASQR84 ASQR85 ASQR86 ASQR87 ASQR88 ASQR89 ASQR90 ASQR91 ASQR92 ASQR93 ASQR94 ASQR95 ASQR96 ASQR97 ASQR98 ASQR99 ASQR100 ASqD1 ASqD2 ASqD3 ASqD4 ASqD5 ASqD6 ASqD7 ASqD8 ASqD9 ASqD10 ASqD11 ASqD12 ASqD13 ASqD14 ASqD15 ASqD16 ASqD17 ASqD18 ASqD19 ASqD20 ASqD21 ASqD22 ASqD23 ASqD24 ASqD25 ASqD26 ASqD27 ASqD28 ASqD29 ASqD30 ASqD31 ASqD32 ASqD33 ASqD34 ASqD35 ASqD36 ASqD37 ASqD38 ASqD39 ASqD40 ASqD41 ASqD42 ASqD43 ASqD44 ASqD45 ASqD46 ASqD47 ASqD48 ASqD49 ASqD50 ASqD51 ASqD52 ASqD53 ASqD54 ASqD55 ASqD56 ASqD57 ASqD58 ASqD59 ASqD60 ASqD61 ASqD62 ASqD63 ASqD64 ASqD65 ASqD66 ASqD67 ASqD68 ASqD69 ASqD70 ASqD71 ASqD72 ASqD73 ASqD74 ASqD75 ASqD76 ASqD77 ASqD78 ASqD79 ASqD80 ASqD81 ASqD82 ASqD83 ASqD84 ASqD85 ASqD86 ASqD87 ASqD88 ASqD89 ASqD90 ASqD91 ASqD92 ASqD93 ASqD94 ASqD95 ASqD96 ASqD97 ASqD98 ASqD99 ASqD100 habitat intercount order1 energy alpha stones condi1 condi2 condi3 condi4 ] ; THE GO BLOCK SETS THE PARAMETERS FOR 3 OR 5 PATTERNS AND THEN CALLS THE PRIMARY SUBROUTINES to go clear-all set counterR -1 repeat 3 [ set counterR counterR + 2 if counterR = 1 [set smooth 100 set peaks 3000 set seed 550 ] if counterR = 2 [set smooth 25 set peaks 5000 set seed 550 ] if counterR = 3 [set smooth 25 set peaks 2000 set seed 550 ] if counterR = 4 [set smooth 10 set peaks 1000 set seed 350 ] if counterR = 5 [set smooth 5 set peaks 1000 set seed 950 ] setup1 setup2 progo ] print 99999 ; outcount1 stop end ; THE SETUP1 SUBROUTINE ASSIGNS A CLIMATE FROM THE GRADIENT 0-1 TO EACH PATCH ;THE RESPONSE OF EACH SPECIES ON EACH PATCH Rix IS ASSIGNED to setup1 set limit 9 random-seed seed set axaxis 100 print date-and-time ask patches [ set pcolor 49.3 ] ask patches [ set ASq1 0 set ASq2 0 set ASq3 0 set ASq4 0 set ASq5 0 set ASq6 0 set ASq7 0 set ASq8 0 set ASq9 0 set ASq10 0 set ASq11 0 set ASq12 0 set ASq13 0 set ASq14 0 set ASq15 0 set ASq16 0 set ASq17 0 set ASq18 0 set ASq19 0 set ASq20 0 set ASq21 0 set ASq22 0 set ASq23 0 set ASq24 0 set ASq25 0 set ASq26 0 set ASq27 0 set ASq28 0 set ASq29 0 set ASq30 0 set ASq31 0 set ASq32 0 set ASq33 0 set ASq34 0 set ASq35 0 set ASq36 0 set ASq37 0 set ASq38 0 set ASq39 0 set ASq40 0 set ASq41 0 set ASq42 0 set ASq43 0 set ASq44 0 set ASq45 0 set ASq46 0 set ASq47 0 set ASq48 0 set ASq49 0 set ASq50 0 set ASq51 0 set ASq52 0 set ASq53 0 set ASq54 0 set ASq55 0 set ASq56 0 set ASq57 0 set ASq58 0 set ASq59 0 set ASq60 0 set ASq61 0 set ASq62 0 set ASq63 0 set ASq64 0 set ASq65 0 set ASq66 0 set ASq67 0 set ASq68 0 set ASq69 0 set ASq70 0 set ASq71 0 set ASq72 0 set ASq73 0 set ASq74 0 set ASq75 0 set ASq76 0 set ASq77 0 set ASq78 0 set ASq79 0 set ASq80 0 set ASq81 0 set ASq82 0 set ASq83 0 set ASq84 0 set ASq85 0 set ASq86 0 set ASq87 0 set ASq88 0 set ASq89 0 set ASq90 0 set ASq91 0 set ASq92 0 set ASq93 0 set ASq94 0 set ASq95 0 set ASq96 0 set ASq97 0 set ASq98 0 set ASq99 0 set ASq100 0 ] ; clear-all set year 0 set counter2 0 set counter3 0 ask patches [set habitat 1 set refuge 0 set energy 1 set counter1 0] repeat peaks [ ask patch random 100 random 100 [set energy 1000 ] ] repeat smooth [diffuse energy 1 ] ;ask patches [set energy ln(energy)] set maxergy max [energy] of patches ; print maxergy set minergy min [energy] of patches ; print minergy set renergy maxergy - minergy if (renergy = 0) [set renergy 1] ask patches [ set climate1 ((energy - minergy) / renergy) ^ 0.5 set climate4 (climate1 * 0.7) + 0.3 ;set climate1 random-normal 0.5 0.2 ;set climate4 (climate1 * 0.8) + 0.2 set climate4 climate1 ] ask patches [ if (pxcor mod 20 = 0 AND pycor mod 20 = 0) [ ask patches in-radius 4.37 [ set climate4 random-float 0.3] ask patch-at 1 4 [set climate4 0.3 + random-float 0.7] ] ] if count patches with [climate4 < 0.3] < 1500 [ repeat (1500 - count patches with [climate4 < 0.3] ) [ ask one-of patches with [climate4 < 0.3] [ ask one-of neighbors [ if climate4 > 0.3 [ set climate4 random-float 0.3 ; set counter1 counter1 - 1 ] ] ] ] ] ] ;THE CLIMATE IS DISTRIBUTED TO APPROXIMATE A NORMAL DISTRIBUTION BUT WITH 1500 COLD MICROREFUGIA PATCHES ; print 7777 ; set counter2 abs(counter1) if count patches with [climate4 < 0.3] > 1500 [ repeat (count patches with [climate4 < 0.3] - 1500) [ set counter2 0 ask one-of patches with [climate4 < 0.3] [ set climate4 0.3 + random-float 0.4 ; set counter1 counter1 - 1 ] ] ] ] ;print count patches with [climate4 < 0.3] if count patches with [climate4 > 0.7] < 1500 [ repeat (1500 - count patches with [climate4 > 0.7] ) [ ask one-of patches with [climate4 < 0.7 AND climate4 > 0.3] [ set climate4 0.7 + random-float 0.3 ; set counter1 counter1 - 1 ] ] ] ] ;if counter1 < 0 [ ; print 7777 ; set counter2 abs(counter1) if count patches with [climate4 > 0.7] > 1500 [ repeat (count patches with [climate4 > 0.7] - 1500) [ set counter2 0 ask one-of patches with [climate4 > 0.7] [ set climate4 0.3 + random-float 0.4 ; set counter1 counter1 - 1 ] ] ] ] print count patches with [climate4 < 0.3] print count patches with [climate4 > 0.7] ; print count patches with [climate4 < 0.3] ; print min [climate4] of patches ; print mean [climate4] of patches ;print max [climate4] of patches ; print standard-deviation [climate4] of patches ask patches [ set pcolor scale-color orange climate4 0 1 ] ask patches [ if climate4 < 0.3 [set refuge 1 set pcolor sky] if climate4 > 0.7 [set pcolor yellow] ] ;EACH SPECIES HAS A GAUSSIAN DISTRIBUTION ON THE CLIMATE GRADIENT FROM WHICH THE RESPONSE IS ; ASSIGNED TO EACH PATCH ask patches [ set ASq1 exp ( ( (( climate4 - 0.01 ) ^ 2 ) / 0.001 ) * -.5) set ASq2 exp ( ( (( climate4 - 0.02 ) ^ 2 ) / 0.001 ) * -.5) set ASq3 exp ( ( (( climate4 - 0.03 ) ^ 2 ) / 0.001 ) * -.5) set ASq4 exp ( ( (( climate4 - 0.04 ) ^ 2 ) / 0.001 ) * -.5) set ASq5 exp ( ( (( climate4 - 0.05 ) ^ 2 ) / 0.001 ) * -.5) set ASq6 exp ( ( (( climate4 - 0.06 ) ^ 2 ) / 0.001 ) * -.5) set ASq7 exp ( ( (( climate4 - 0.07 ) ^ 2 ) / 0.001 ) * -.5) set ASq8 exp ( ( (( climate4 - 0.08 ) ^ 2 ) / 0.001 ) * -.5) set ASq9 exp ( ( (( climate4 - 0.004 ) ^ 2 ) / 0.001 ) * -.5) set ASq10 exp ( ( (( climate4 - 0.1 ) ^ 2 ) / 0.001 ) * -.5) set ASq11 exp ( ( (( climate4 - 0.11 ) ^ 2 ) / 0.001 ) * -.5) set ASq12 exp ( ( (( climate4 - 0.12 ) ^ 2 ) / 0.001 ) * -.5) set ASq13 exp ( ( (( climate4 - 0.13 ) ^ 2 ) / 0.001 ) * -.5) set ASq14 exp ( ( (( climate4 - 0.14 ) ^ 2 ) / 0.001 ) * -.5) set ASq15 exp ( ( (( climate4 - 0.15 ) ^ 2 ) / 0.001 ) * -.5) set ASq16 exp ( ( (( climate4 - 0.16 ) ^ 2 ) / 0.001 ) * -.5) set ASq17 exp ( ( (( climate4 - 0.17 ) ^ 2 ) / 0.001 ) * -.5) set ASq18 exp ( ( (( climate4 - 0.18 ) ^ 2 ) / 0.001 ) * -.5) set ASq19 exp ( ( (( climate4 - 0.19 ) ^ 2 ) / 0.001 ) * -.5) set ASq20 exp ( ( (( climate4 - 0.2 ) ^ 2 ) / 0.001 ) * -.5) set ASq21 exp ( ( (( climate4 - 0.21 ) ^ 2 ) / 0.001 ) * -.5) set ASq22 exp ( ( (( climate4 - 0.22 ) ^ 2 ) / 0.001 ) * -.5) set ASq23 exp ( ( (( climate4 - 0.23 ) ^ 2 ) / 0.001 ) * -.5) set ASq24 exp ( ( (( climate4 - 0.24 ) ^ 2 ) / 0.001 ) * -.5) set ASq25 exp ( ( (( climate4 - 0.25 ) ^ 2 ) / 0.001 ) * -.5) set ASq26 exp ( ( (( climate4 - 0.26 ) ^ 2 ) / 0.001 ) * -.5) set ASq27 exp ( ( (( climate4 - 0.27 ) ^ 2 ) / 0.001 ) * -.5) set ASq28 exp ( ( (( climate4 - 0.28 ) ^ 2 ) / 0.001 ) * -.5) set ASq29 exp ( ( (( climate4 - 0.29 ) ^ 2 ) / 0.001 ) * -.5) set ASq30 exp ( ( (( climate4 - 0.39 ) ^ 2 ) / 0.001 ) * -.5) set ASq31 exp ( ( (( climate4 - 0.31 ) ^ 2 ) / 0.001 ) * -.5) set ASq32 exp ( ( (( climate4 - 0.32 ) ^ 2 ) / 0.001 ) * -.5) set ASq33 exp ( ( (( climate4 - 0.33 ) ^ 2 ) / 0.001 ) * -.5) set ASq34 exp ( ( (( climate4 - 0.34 ) ^ 2 ) / 0.001 ) * -.5) set ASq35 exp ( ( (( climate4 - 0.35 ) ^ 2 ) / 0.001 ) * -.5) set ASq36 exp ( ( (( climate4 - 0.36 ) ^ 2 ) / 0.001 ) * -.5) set ASq37 exp ( ( (( climate4 - 0.37 ) ^ 2 ) / 0.001 ) * -.5) set ASq38 exp ( ( (( climate4 - 0.38 ) ^ 2 ) / 0.001 ) * -.5) set ASq39 exp ( ( (( climate4 - 0.39 ) ^ 2 ) / 0.001 ) * -.5) set ASq40 exp ( ( (( climate4 - 0.40 ) ^ 2 ) / 0.001 ) * -.5) set ASq41 exp ( ( (( climate4 - 0.41 ) ^ 2 ) / 0.001 ) * -.5) set ASq42 exp ( ( (( climate4 - 0.42 ) ^ 2 ) / 0.001 ) * -.5) set ASq43 exp ( ( (( climate4 - 0.43 ) ^ 2 ) / 0.001 ) * -.5) set ASq44 exp ( ( (( climate4 - 0.44 ) ^ 2 ) / 0.001 ) * -.5) set ASq45 exp ( ( (( climate4 - 0.45 ) ^ 2 ) / 0.001 ) * -.5) set ASq46 exp ( ( (( climate4 - 0.46 ) ^ 2 ) / 0.001 ) * -.5) set ASq47 exp ( ( (( climate4 - 0.47 ) ^ 2 ) / 0.001 ) * -.5) set ASq48 exp ( ( (( climate4 - 0.48 ) ^ 2 ) / 0.001 ) * -.5) set ASq49 exp ( ( (( climate4 - 0.49 ) ^ 2 ) / 0.001 ) * -.5) set ASq50 exp ( ( (( climate4 - 0.5 ) ^ 2 ) / 0.001 ) * -.5) set ASq51 exp ( ( (( climate4 - 0.51 ) ^ 2 ) / 0.001 ) * -.5) set ASq52 exp ( ( (( climate4 - 0.52 ) ^ 2 ) / 0.001 ) * -.5) set ASq53 exp ( ( (( climate4 - 0.53 ) ^ 2 ) / 0.001 ) * -.5) set ASq54 exp ( ( (( climate4 - 0.54 ) ^ 2 ) / 0.001 ) * -.5) set ASq55 exp ( ( (( climate4 - 0.55 ) ^ 2 ) / 0.001 ) * -.5) set ASq56 exp ( ( (( climate4 - 0.56 ) ^ 2 ) / 0.001 ) * -.5) set ASq57 exp ( ( (( climate4 - 0.57 ) ^ 2 ) / 0.001 ) * -.5) set ASq58 exp ( ( (( climate4 - 0.58 ) ^ 2 ) / 0.001 ) * -.5) set ASq59 exp ( ( (( climate4 - 0.59 ) ^ 2 ) / 0.001 ) * -.5) set ASq60 exp ( ( (( climate4 - 0.60 ) ^ 2 ) / 0.001 ) * -.5) set ASq61 exp ( ( (( climate4 - 0.61 ) ^ 2 ) / 0.001 ) * -.5) set ASq62 exp ( ( (( climate4 - 0.62 ) ^ 2 ) / 0.001 ) * -.5) set ASq63 exp ( ( (( climate4 - 0.63 ) ^ 2 ) / 0.001 ) * -.5) set ASq64 exp ( ( (( climate4 - 0.64 ) ^ 2 ) / 0.001 ) * -.5) set ASq65 exp ( ( (( climate4 - 0.65 ) ^ 2 ) / 0.001 ) * -.5) set ASq66 exp ( ( (( climate4 - 0.66 ) ^ 2 ) / 0.001 ) * -.5) set ASq67 exp ( ( (( climate4 - 0.67 ) ^ 2 ) / 0.001 ) * -.5) set ASq68 exp ( ( (( climate4 - 0.68 ) ^ 2 ) / 0.001 ) * -.5) set ASq69 exp ( ( (( climate4 - 0.69 ) ^ 2 ) / 0.001 ) * -.5) set ASq70 exp ( ( (( climate4 - 0.70 ) ^ 2 ) / 0.001 ) * -.5) set ASq71 exp ( ( (( climate4 - 0.71 ) ^ 2 ) / 0.001 ) * -.5) set ASq72 exp ( ( (( climate4 - 0.72 ) ^ 2 ) / 0.001 ) * -.5) set ASq73 exp ( ( (( climate4 - 0.73 ) ^ 2 ) / 0.001 ) * -.5) set ASq74 exp ( ( (( climate4 - 0.74 ) ^ 2 ) / 0.001 ) * -.5) set ASq75 exp ( ( (( climate4 - 0.75 ) ^ 2 ) / 0.001 ) * -.5) set ASq76 exp ( ( (( climate4 - 0.76 ) ^ 2 ) / 0.001 ) * -.5) set ASq77 exp ( ( (( climate4 - 0.77 ) ^ 2 ) / 0.001 ) * -.5) set ASq78 exp ( ( (( climate4 - 0.78 ) ^ 2 ) / 0.001 ) * -.5) set ASq79 exp ( ( (( climate4 - 0.79 ) ^ 2 ) / 0.001 ) * -.5) set ASq80 exp ( ( (( climate4 - 0.80 ) ^ 2 ) / 0.001 ) * -.5) set ASq81 exp ( ( (( climate4 - 0.81 ) ^ 2 ) / 0.001 ) * -.5) set ASq82 exp ( ( (( climate4 - 0.82 ) ^ 2 ) / 0.001 ) * -.5) set ASq83 exp ( ( (( climate4 - 0.83 ) ^ 2 ) / 0.001 ) * -.5) set ASq84 exp ( ( (( climate4 - 0.84 ) ^ 2 ) / 0.001 ) * -.5) set ASq85 exp ( ( (( climate4 - 0.85 ) ^ 2 ) / 0.001 ) * -.5) set ASq86 exp ( ( (( climate4 - 0.86 ) ^ 2 ) / 0.001 ) * -.5) set ASq87 exp ( ( (( climate4 - 0.87 ) ^ 2 ) / 0.001 ) * -.5) set ASq88 exp ( ( (( climate4 - 0.88 ) ^ 2 ) / 0.001 ) * -.5) set ASq89 exp ( ( (( climate4 - 0.89 ) ^ 2 ) / 0.001 ) * -.5) set ASq90 exp ( ( (( climate4 - 0.9 ) ^ 2 ) / 0.001 ) * -.5) set ASq91 exp ( ( (( climate4 - 0.91 ) ^ 2 ) / 0.001 ) * -.5) set ASq92 exp ( ( (( climate4 - 0.92 ) ^ 2 ) / 0.001 ) * -.5) set ASq93 exp ( ( (( climate4 - 0.93 ) ^ 2 ) / 0.001 ) * -.5) set ASq94 exp ( ( (( climate4 - 0.94 ) ^ 2 ) / 0.001 ) * -.5) set ASq95 exp ( ( (( climate4 - 0.95 ) ^ 2 ) / 0.001 ) * -.5) set ASq96 exp ( ( (( climate4 - 0.96 ) ^ 2 ) / 0.001 ) * -.5) set ASq97 exp ( ( (( climate4 - 0.97 ) ^ 2 ) / 0.001 ) * -.5) set ASq98 exp ( ( (( climate4 - 0.98 ) ^ 2 ) / 0.001 ) * -.5) set ASq99 exp ( ( (( climate4 - 0.99 ) ^ 2 ) / 0.001 ) * -.5) set ASq100 exp ( ( (( climate4 - 1) ^ 2 ) / 0.001 ) * -.5) ; if (pxcor = 99) [print ASq51] ] set seed 550 reset-ticks end ; THE SETUP2 SUBROUTINE CREATES THE INITIAL DISTRIBUTION OF SPECIES ON THE PATCHES ACCORDING TO ; THEIR RESPONSE TO CLIMATE to setup2 random-seed seed repeat 5 [ ask patches [ if (random-float 1 < Asq1 ) [ sprout-Sp1s 1 [ set size 1 set deathv 0 set age random 100 + 50 set color 5 ]] if (random-float 1 < Asq2 ) [ sprout-Sp2s 1 [ set size 1 set deathv 0 set age random 100 + 50 set color 5 ]] if (random-float 1 < Asq3) [ sprout-Sp3s 1 [ set size 1 set deathv 0 set age random 100 + 50 set color 5 ]] if (random-float 1 < Asq4) [ sprout-Sp4s 1 [ set size 1 set deathv 0 set age random 100 + 50 set color 5 ]] if (random-float 1 < Asq5) [ sprout-Sp5s 1 [ set size 1 set deathv 0 set age random 100 + 50 set color 5 ]] if (random-float 1 < Asq6) [ sprout-Sp6s 1 [ set size 1 set deathv 0 set age random 100 + 50 set color 5 ]] if (random-float 1 < Asq7) [ sprout-Sp7s 1 [ set size 1 set deathv 0 set age random 100 + 50 set color 5 ; print 111 ]] if (random-float 1 < Asq8) [ sprout-Sp8s 1 [ set size 1 set deathv 0 set age random 100 + 50 set color 5 ]] if (random-float 1 < Asq9) [ sprout-Sp9s 1 [ set size 1 set deathv 0 set age random 100 + 50 set color 5 ]] if (random-float 1 < Asq10) [ sprout-Sp10s 1 [ set size 1 set deathv 0 set age random 100 + 50 set color 5 ]] if (random-float 1 < Asq11) [ sprout-Sp11s 1 [ set size 1 set deathv 0 set age random 100 + 50 set color 15 ]] if (random-float 1 < Asq12) [ sprout-Sp12s 1 [ set size 1 set deathv 0 set age random 100 + 50 set color 15 ]] if (random-float 1 < Asq13) [ sprout-Sp13s 1 [ set size 1 set deathv 0 set age random 100 + 50 set color 15 ] ] if (random-float 1 < Asq14) [ sprout-Sp14s 1 [ set size 1 set deathv 0 set age random 100 + 50 set color 15 ] ] if (random-float 1 < Asq15) [ sprout-Sp15s 1 [ set size 1 set deathv 0 set age random 100 + 50 set color 15 ] ] if (random-float 1 < Asq16) [ sprout-Sp16s 1 [ set size 1 set deathv 0 set age random 100 + 50 set color 25 ] ] if (random-float 1 < Asq17) [ sprout-Sp17s 1 [ set size 1 set deathv 0 set age random 100 + 50 set color 25 ] ] if (random-float 1 < Asq18) [ sprout-Sp18s 1 [ set size 1 set deathv 0 set age random 100 + 50 set color 25 ] ] if (random-float 1 < Asq19) [ sprout-Sp19s 1 [ set size 1 set deathv 0 set age random 100 + 50 set color 25 ] ] if (random-float 1 < Asq20) [ sprout-Sp20s 1 [ set size 1 set deathv 0 set age random 100 + 50 set color 25 ] ] if (random-float 1 < Asq21) [ sprout-Sp21s 1 [ set size 1 set deathv 0 set age random 100 + 50 set color 25 ] ] if (random-float 1 < Asq22) [ sprout-Sp22s 1 [ set size 1 set deathv 0 set age random 100 + 50 set color 25 ] ] if (random-float 1 < Asq23 ) [ sprout-Sp23s 1 [ set size 1 set deathv 0 set age random 100 + 50 set color 25 ]] if (random-float 1 < Asq24 ) [ sprout-Sp24s 1 [ set size 1 set deathv 0 set age random 100 + 50 set color 25 ]] if (random-float 1 < Asq25 ) [ sprout-Sp25s 1 [ set size 1 set deathv 0 set age random 100 + 50 set color 25 ]] if (random-float 1 < Asq26) [ sprout-Sp26s 1 [ set size 1 set deathv 0 set age random 100 + 50 set color 35 ]] if (random-float 1 < Asq27) [ sprout-Sp27s 1 [ set size 1 set deathv 0 set age random 100 + 50 set color 35 ]] if (random-float 1 < Asq28) [ sprout-Sp28s 1 [ set size 1 set deathv 0 set age random 100 + 50 set color 35 ]] if (random-float 1 < Asq29) [ sprout-Sp29s 1 [ set size 1 set deathv 0 set age random 100 + 50 set color 35 ]] if (random-float 1 < Asq30) [ sprout-Sp30s 1 [ set size 1 set deathv 0 set age random 100 + 50 set color 35 ; print 111 ]] if (random-float 1 < Asq31) [ sprout-Sp31s 1 [ set size 1 set deathv 0 set age random 100 + 50 set color 35 ]] if (random-float 1 < Asq32) [ sprout-Sp32s 1 [ set size 1 set deathv 0 set age random 100 + 50 set color 35 ]] if (random-float 1 < Asq33) [ sprout-Sp33s 1 [ set size 1 set deathv 0 set age random 100 + 50 set color 35 ]] if (random-float 1 < Asq34) [ sprout-Sp34s 1 [ set size 1 set deathv 0 set age random 100 + 50 set color 35 ]] if (random-float 1 < Asq35) [ sprout-Sp35s 1 [ set size 1 set deathv 0 set age random 100 + 50 set color 35 ]] if (random-float 1 < Asq36) [ sprout-Sp36s 1 [ set size 1 set deathv 0 set age random 100 + 50 set color 45 ] ] if (random-float 1 < Asq37) [ sprout-Sp37s 1 [ set size 1 set deathv 0 set age random 100 + 50 set color 45 ] ] if (random-float 1 < Asq38) [ sprout-Sp38s 1 [ set size 1 set deathv 0 set age random 100 + 50 set color 45 ] ] if (random-float 1 < Asq39) [ sprout-Sp39s 1 [ set size 1 set deathv 0 set age random 100 + 50 set color 45 ] ] if (random-float 1 < Asq40) [ sprout-Sp40s 1 [ set size 1 set deathv 0 set age random 100 + 50 set color 45 ; print 111 ]] if (random-float 1 < Asq41) [ sprout-Sp41s 1 [ set size 1 set deathv 0 set age random 100 + 50 set color 45 ]] if (random-float 1 < Asq42) [ sprout-Sp42s 1 [ set size 1 set deathv 0 set age random 100 + 50 set color 45 ]] if (random-float 1 < Asq43) [ sprout-Sp43s 1 [ set size 1 set deathv 0 set age random 100 + 50 set color 45 ]] if (random-float 1 < Asq44) [ sprout-Sp44s 1 [ set size 1 set deathv 0 set age random 100 + 50 set color 45 ]] if (random-float 1 < Asq45) [ sprout-Sp45s 1 [ set size 1 set deathv 0 set age random 100 + 50 set color 45 ]] if (random-float 1 < Asq46) [ sprout-Sp46s 1 [ set size 1 set deathv 0 set age random 100 + 50 set color 55 ] ] if (random-float 1 < Asq47) [ sprout-Sp47s 1 [ set size 1 set deathv 0 set age random 100 + 50 set color 55 ] ] if (random-float 1 < Asq48) [ sprout-Sp48s 1 [ set size 1 set deathv 0 set age random 100 + 50 set color 55 ] ] if (random-float 1 < Asq49) [ sprout-Sp49s 1 [ set size 1 set deathv 0 set age random 100 + 50 set color 55 ] ] if (random-float 1 < Asq50) [ sprout-Sp50s 1 [ set size 1 set deathv 0 set age random 100 + 50 set color 55 ; print 111 ]] if (random-float 1 < Asq51) [ sprout-Sp51s 1 [ set size 1 set deathv 0 set age random 100 + 50 set color 55 ]] if (random-float 1 < Asq52) [ sprout-Sp52s 1 [ set size 1 set deathv 0 set age random 100 + 50 set color 55 ]] if (random-float 1 < Asq53) [ sprout-Sp53s 1 [ set size 1 set deathv 0 set age random 100 + 50 set color 55 ]] if (random-float 1 < Asq54) [ sprout-Sp54s 1 [ set size 1 set deathv 0 set age random 100 + 50 set color 55 ]] if (random-float 1 < Asq55) [ sprout-Sp55s 1 [ set size 1 set deathv 0 set age random 100 + 50 set color 55 ]] if (random-float 1 < Asq56) [ sprout-Sp56s 1 [ set size 1 set deathv 0 set age random 100 + 50 set color 65 ] ] if (random-float 1 < Asq57) [ sprout-Sp57s 1 [ set size 1 set deathv 0 set age random 100 + 50 set color 65 ] ] if (random-float 1 < Asq58) [ sprout-Sp58s 1 [ set size 1 set deathv 0 set age random 100 + 50 set color 65 ] ] if (random-float 1 < Asq59) [ sprout-Sp59s 1 [ set size 1 set deathv 0 set age random 100 + 50 set color 65 ] ] if (random-float 1 < Asq60) [ sprout-Sp60s 1 [ set size 1 set deathv 0 set age random 100 + 50 set color 65 ; print 111 ]] if (random-float 1 < Asq61) [ sprout-Sp61s 1 [ set size 1 set deathv 0 set age random 100 + 50 set color 65 ]] if (random-float 1 < Asq62) [ sprout-Sp62s 1 [ set size 1 set deathv 0 set age random 100 + 50 set color 65 ]] if (random-float 1 < Asq63) [ sprout-Sp63s 1 [ set size 1 set deathv 0 set age random 100 + 50 set color 65 ]] if (random-float 1 < Asq64) [ sprout-Sp64s 1 [ set size 1 set deathv 0 set age random 100 + 50 set color 65 ]] if (random-float 1 < Asq65) [ sprout-Sp65s 1 [ set size 1 set deathv 0 set age random 100 + 50 set color 65 ]] if (random-float 1 < Asq66) [ sprout-Sp66s 1 [ set size 1 set deathv 0 set age random 100 + 50 set color 75 ] ] if (random-float 1 < Asq67) [ sprout-Sp67s 1 [ set size 1 set deathv 0 set age random 100 + 50 set color 75 ] ] if (random-float 1 < Asq68) [ sprout-Sp68s 1 [ set size 1 set deathv 0 set age random 100 + 50 set color 75 ] ] if (random-float 1 < Asq69) [ sprout-Sp69s 1 [ set size 1 set deathv 0 set age random 100 + 50 set color 75 ] ] if (random-float 1 < Asq70) [ sprout-Sp70s 1 [ set size 1 set deathv 0 set age random 100 + 50 set color 75 ; print 111 ]] if (random-float 1 < Asq71) [ sprout-Sp71s 1 [ set size 1 set deathv 0 set age random 100 + 50 set color 75 ]] if (random-float 1 < Asq72) [ sprout-Sp72s 1 [ set size 1 set deathv 0 set age random 100 + 50 set color 75 ]] if (random-float 1 < Asq73) [ sprout-Sp73s 1 [ set size 1 set deathv 0 set age random 100 + 50 set color 75 ]] if (random-float 1 < Asq74) [ sprout-Sp74s 1 [ set size 1 set deathv 0 set age random 100 + 50 set color 75 ]] if (random-float 1 < Asq75) [ sprout-Sp75s 1 [ set size 1 set deathv 0 set age random 100 + 50 set color 75 ]] if (random-float 1 < Asq76) [ sprout-Sp76s 1 [ set size 1 set deathv 0 set age random 100 + 50 set color 85 ] ] if (random-float 1 < Asq77) [ sprout-Sp77s 1 [ set size 1 set deathv 0 set age random 100 + 50 set color 85 ] ] if (random-float 1 < Asq78) [ sprout-Sp78s 1 [ set size 1 set deathv 0 set age random 100 + 50 set color 85 ] ] if (random-float 1 < Asq79) [ sprout-Sp79s 1 [ set size 1 set deathv 0 set age random 100 + 50 set color 85 ] ] if (random-float 1 < Asq80) [ sprout-Sp80s 1 [ set size 1 set deathv 0 set age random 100 + 50 set color 85 ]] if (random-float 1 < Asq81) [ sprout-Sp81s 1 [ set size 1 set deathv 0 set age random 100 + 50 set color 85 ]] if (random-float 1 < Asq82) [ sprout-Sp82s 1 [ set size 1 set deathv 0 set age random 100 + 50 set color 85 ]] if (random-float 1 < Asq83) [ sprout-Sp83s 1 [ set size 1 set deathv 0 set age random 100 + 50 set color 85 ]] if (random-float 1 < Asq84) [ sprout-Sp84s 1 [ set size 1 set deathv 0 set age random 100 + 50 set color 85 ]] if (random-float 1 < Asq85) [ sprout-Sp85s 1 [ set size 1 set deathv 0 set age random 100 + 50 set color 85 ]] if (random-float 1 < Asq86) [ sprout-Sp86s 1 [ set size 1 set deathv 0 set age random 100 + 50 set color 95 ] ] if (random-float 1 < Asq87) [ sprout-Sp87s 1 [ set size 1 set deathv 0 set age random 100 + 50 set color 95 ] ] if (random-float 1 < Asq88) [ sprout-Sp88s 1 [ set size 1 set deathv 0 set age random 100 + 50 set color 95 ] ] if (random-float 1 < Asq89) [ sprout-Sp89s 1 [ set size 1 set deathv 0 set age random 100 + 50 set color 95 ] ] if (random-float 1 < Asq90) [ sprout-Sp90s 1 [ set size 1 set deathv 0 set age random 100 + 50 set color 95 ; print 111 ]] if (random-float 1 < Asq91) [ sprout-Sp91s 1 [ set size 1 set deathv 0 set age random 100 + 50 set color 95 ]] if (random-float 1 < Asq92) [ sprout-Sp92s 1 [ set size 1 set deathv 0 set age random 100 + 50 set color 95 ]] if (random-float 1 < Asq93) [ sprout-Sp93s 1 [ set size 1 set deathv 0 set age random 100 + 50 set color 95 ]] if (random-float 1 < Asq94) [ sprout-Sp94s 1 [ set size 1 set deathv 0 set age random 100 + 50 set color 95 ]] if (random-float 1 < Asq95) [ sprout-Sp95s 1 [ set size 1 set deathv 0 set age random 100 + 50 set color 95 ]] if (random-float 1 < Asq96) [ sprout-Sp96s 1 [ set size 1 set deathv 0 set age random 100 + 50 set color 105 ] ] if (random-float 1 < Asq97) [ sprout-Sp97s 1 [ set size 1 set deathv 0 set age random 100 + 50 set color 105 ] ] if (random-float 1 < Asq98) [ sprout-Sp98s 1 [ set size 1 set deathv 0 set age random 100 + 50 set color 105 ] ] if (random-float 1 < Asq99) [ sprout-Sp99s 1 [ set size 1 set deathv 0 set age random 100 + 50 set color 105 ] ] if (random-float 1 < Asq100) [ sprout-Sp100s 1 [ set size 1 set deathv 0 set age random 100 + 50 set color 105 ] ] ] ; A LIMIT OF 10 INDIVIDUALS PER PATCH IS MAINTAINED ask turtles [ if (count other turtles-here > limit) [ die] ] set counterN count turtles ] ;outcount2 reset-ticks end ; THE PROGO SUBROUTINE CALLS THE PROCEDURES THAT EXECUTE THE PROGRAM AND PRINTS THE RESULTS IN THE ; OBSERVER BLOCK OF THE gui to progo random-seed seed + 50 set year 0 repeat 200 [ ager ask turtles [ if (count other turtles-here > limit) [ die] ] if (year > 50 AND year < 151 ) [ shrink ; print mean [ASQA5] of patches ] ; if year = 201 [ outcount3] compete estab ubi death ;if year = 200 [ rich print gamma ; ] tick ] outcount1 ; outcount3 end to ager set year year + 1 ask turtles [set age age + 1] ask patches [ set habitat 1 if count turtles-here = 0 [set habitat 0] ] set counterQ count patches with [habitat = 1] end ; THE COMPETE SUBROUTINE CREATES A MODIFIER THAT MULTIPLIES Rix BASED ON PATCH DENSITY to compete random-seed seed + 100 ask patches [ set roomA 1 ;if (count turtles-here = 0) [set room 1] if (count turtles-here > 0) [ set roomA 1 - .05 * count turtles-here set roomD 1 - .02 * count turtles-here set roomR 1 - .1 * count turtles-here ] ] ask patches [ ; if (pxcor = 0) [print room] set ASqR1 ASq1 * roomR set ASqR2 ASq2 * roomR set ASqR3 ASq3 * roomR set ASqR4 ASq4 * roomR set ASqR5 ASq5 * roomR set ASqR6 ASq6 * roomR set ASqR7 ASq7 * roomR set ASqR8 ASq8 * roomR set ASqR9 ASq9 * roomR set ASqR10 ASq10 * roomR set ASQR11 ASq11 * roomR set ASQR12 ASq12 * roomR set ASQR13 ASq13 * roomR set ASQR14 ASq14 * roomR set ASQR15 ASq15 * roomR set ASQR16 ASq16 * roomR set ASQR17 ASq17 * roomR set ASQR18 ASq18 * roomR set ASQR19 ASq19 * roomR set ASQR20 ASq20 * roomR set ASQR21 ASq21 * roomR set ASQR22 ASq22 * roomR set ASQR23 ASq23 * roomR set ASQR24 ASq24 * roomR set ASQR25 ASq25 * roomR set ASQR26 ASq26 * roomR set ASQR27 ASq27 * roomR set ASQR28 ASq28 * roomR set ASQR29 ASq29 * roomR set ASQR30 ASq30 * roomR set ASQR31 ASq31 * roomR set ASQR32 ASq32 * roomR set ASQR33 ASq33 * roomR set ASQR34 ASq34 * roomR set ASQR35 ASq35 * roomR set ASQR36 ASq36 * roomR set ASQR37 ASq37 * roomR set ASQR38 ASq38 * roomR set ASQR39 ASq39 * roomR set ASQR40 ASq40 * roomR set ASQR41 ASq41 * roomR set ASQR42 ASq42 * roomR set ASQR43 ASq43 * roomR set ASQR44 ASq44 * roomR set ASQR45 ASq45 * roomR set ASQR46 ASq46 * roomR set ASQR47 ASq47 * roomR set ASQR48 ASq48 * roomR set ASQR49 ASq49 * roomR set ASQR50 ASq50 * roomR set ASQR51 ASq51 * roomR set ASQR52 ASq52 * roomR set ASQR53 ASq53 * roomR set ASQR54 ASq54 * roomR set ASQR55 ASq55 * roomR set ASQR56 ASq56 * roomR set ASQR57 ASq57 * roomR set ASQR58 ASq58 * roomR set ASqR59 ASq59 * roomR set ASQR60 ASq60 * roomR set ASQR61 ASq61 * roomR set ASQR62 ASq62 * roomR set ASQR63 ASq63 * roomR set ASQR64 ASq64 * roomR set ASQR65 ASq65 * roomR set ASQR66 ASq66 * roomR set ASQR67 ASq67 * roomR set ASQR68 ASq68 * roomR set ASQR69 ASq69 * roomR set ASQR70 ASq70 * roomR set ASQR71 ASq71 * roomR set ASQR72 ASq72 * roomR set ASQR73 ASq73 * roomR set ASQR74 ASq74 * roomR set ASQR75 ASq75 * roomR set ASQR76 ASq76 * roomR set ASQR77 ASq77 * roomR set ASQR78 ASq78 * roomR set ASQR79 ASq79 * roomR set ASQR80 ASq80 * roomR set ASQR81 ASq81 * roomR set ASQR82 ASq82 * roomR set ASQR83 ASq83 * roomR set ASQR84 ASq84 * roomR set ASQR85 ASq85 * roomR set ASQR86 ASq86 * roomR set ASQR87 ASq87 * roomR set ASQR88 ASq88 * roomR set ASQR89 ASq89 * roomR set ASQR90 ASq90 * roomR set ASQR91 ASq91 * roomR set ASQR92 ASq92 * roomR set ASQR93 ASq93 * roomR set ASQR94 ASq94 * roomR set ASQR95 ASq95 * roomR set ASQR96 ASq96 * roomR set ASQR97 ASq97 * roomR set ASQR98 ASq98 * roomR set ASQR99 ASq99 * roomR set ASqR100 ASq100 * roomR set ASqD1 ASq1 * roomD set ASqD2 ASq2 * roomD set ASqD3 ASq3 * roomD set ASqD4 ASq4 * roomD set ASqD5 ASq5 * roomD set ASqD6 ASq6 * roomD set ASqD7 ASq7 * roomD set ASqD8 ASq8 * roomD set ASqD9 ASq9 * roomD set ASqD10 ASq10 * roomD set ASqD11 ASq11 * roomD set ASqD12 ASq12 * roomD set ASqD13 ASq13 * roomD set ASqD14 ASq14 * roomD set ASqD15 ASq15 * roomD set ASqD16 ASq16 * roomD set ASqD17 ASq17 * roomD set ASqD18 ASq18 * roomD set ASqD19 ASq19 * roomD set ASqD20 ASq20 * roomD set ASqD21 ASq21 * roomD set ASqD22 ASq22 * roomD set ASqD23 ASq23 * roomD set ASqD24 ASq24 * roomD set ASqD25 ASq25 * roomD set ASqD26 ASq26 * roomD set ASqD27 ASq27 * roomD set ASqD28 ASq28 * roomD set ASqD29 ASq29 * roomD set ASqD30 ASq30 * roomD set ASqD31 ASq31 * roomD set ASqD32 ASq32 * roomD set ASqD33 ASq33 * roomD set ASqD34 ASq34 * roomD set ASqD35 ASq35 * roomD set ASqD36 ASq36 * roomD set ASqD37 ASq37 * roomD set ASqD38 ASq38 * roomD set ASqD39 ASq39 * roomD set ASqD40 ASq40 * roomD set ASqD41 ASq41 * roomD set ASqD42 ASq42 * roomD set ASqD43 ASq43 * roomD set ASqD44 ASq44 * roomD set ASqD45 ASq45 * roomD set ASqD46 ASq46 * roomD set ASqD47 ASq47 * roomD set ASqD48 ASq48 * roomD set ASqD49 ASq49 * roomD set ASqD50 ASq50 * roomD set ASqD51 ASq51 * roomD set ASqD52 ASq52 * roomD set ASqD53 ASq53 * roomD set ASqD54 ASq54 * roomD set ASqD55 ASq55 * roomD set ASqD56 ASq56 * roomD set ASqD57 ASq57 * roomD set ASqD58 ASq58 * roomD set ASqD59 ASq59 * roomD set ASqD60 ASq60 * roomD set ASqD61 ASq61 * roomD set ASqD62 ASq62 * roomD set ASqD63 ASq63 * roomD set ASqD64 ASq64 * roomD set ASqD65 ASq65 * roomD set ASqD66 ASq66 * roomD set ASqD67 ASq67 * roomD set ASqD68 ASq68 * roomD set ASqD69 ASq69 * roomD set ASqD70 ASq70 * roomD set ASqD71 ASq71 * roomD set ASqD72 ASq72 * roomD set ASqD73 ASq73 * roomD set ASqD74 ASq74 * roomD set ASqD75 ASq75 * roomD set ASqD76 ASq76 * roomD set ASqD77 ASq77 * roomD set ASqD78 ASq78 * roomD set ASqD79 ASq79 * roomD set ASqD80 ASq80 * roomD set ASqD81 ASq81 * roomD set ASqD82 ASq82 * roomD set ASqD83 ASq83 * roomD set ASqD84 ASq84 * roomD set ASqD85 ASq85 * roomD set ASqD86 ASq86 * roomD set ASqD87 ASq87 * roomD set ASqD88 ASq88 * roomD set ASqD89 ASq89 * roomD set ASqD90 ASq90 * roomD set ASqD91 ASq91 * roomD set ASqD92 ASq92 * roomD set ASqD93 ASq93 * roomD set ASqD94 ASq94 * roomD set ASqD95 ASq95 * roomD set ASqD96 ASq96 * roomD set ASqD97 ASq97 * roomD set ASqD98 ASq98 * roomD set ASqD99 ASq99 * roomD set ASqD100 ASq100 * roomD ] end ; THE SHRINK SUBROUTINE RESETS Rix AS CLIMATE CHANGES ; IF REFUGE !=O THE VALUE USED DETERMINES THE BUFFER EFFECTIVENESS to shrink ; THE CHANGE FOR THE SLOPE IS 0.005 / YR ; THE CHANGES TO ADD TO THE REFUGIA DEPEND ON BUFFER EFFECTIVENESS: ; 100% 0 ; 90% 0.0005 ; 80% 0.001 ; 70% 0.0015 ; 60% 0.002 ; 50% 0.0025 ; 40% 0.003 ; 30% 0.0035 ; 20% 0.004 ; 10% 0.0045 ; 0% 0.005 ask patches [ ; print climate1 ifelse (refuge = 0) [set climate4 climate4 + 0.005] [set climate4 climate4 + 0.0025] ;.5b ; [set climate4 climate4 + 0.00125] ;set climate4 climate4 + 0.005 ] ;print climate1 ;set habitat ask patches [ set ASq1 exp ( ( (( climate4 - 0.01 ) ^ 2 ) / 0.001 ) * -.5) set ASq2 exp ( ( (( climate4 - 0.02 ) ^ 2 ) / 0.001 ) * -.5) set ASq3 exp ( ( (( climate4 - 0.03 ) ^ 2 ) / 0.001 ) * -.5) set ASq4 exp ( ( (( climate4 - 0.04 ) ^ 2 ) / 0.001 ) * -.5) set ASq5 exp ( ( (( climate4 - 0.05 ) ^ 2 ) / 0.001 ) * -.5) set ASq6 exp ( ( (( climate4 - 0.06 ) ^ 2 ) / 0.001 ) * -.5) set ASq7 exp ( ( (( climate4 - 0.07 ) ^ 2 ) / 0.001 ) * -.5) set ASq8 exp ( ( (( climate4 - 0.08 ) ^ 2 ) / 0.001 ) * -.5) set ASq9 exp ( ( (( climate4 - 0.09 ) ^ 2 ) / 0.001 ) * -.5) set ASq10 exp ( ( (( climate4 - 0.1 ) ^ 2 ) / 0.001 ) * -.5) set ASq11 exp ( ( (( climate4 - 0.11 ) ^ 2 ) / 0.001 ) * -.5) set ASq12 exp ( ( (( climate4 - 0.12 ) ^ 2 ) / 0.001 ) * -.5) set ASq13 exp ( ( (( climate4 - 0.13 ) ^ 2 ) / 0.001 ) * -.5) set ASq14 exp ( ( (( climate4 - 0.14 ) ^ 2 ) / 0.001 ) * -.5) set ASq15 exp ( ( (( climate4 - 0.15 ) ^ 2 ) / 0.001 ) * -.5) set ASq16 exp ( ( (( climate4 - 0.16 ) ^ 2 ) / 0.001 ) * -.5) set ASq17 exp ( ( (( climate4 - 0.17 ) ^ 2 ) / 0.001 ) * -.5) set ASq18 exp ( ( (( climate4 - 0.18 ) ^ 2 ) / 0.001 ) * -.5) set ASq19 exp ( ( (( climate4 - 0.19 ) ^ 2 ) / 0.001 ) * -.5) set ASq20 exp ( ( (( climate4 - 0.2 ) ^ 2 ) / 0.001 ) * -.5) set ASq21 exp ( ( (( climate4 - 0.21 ) ^ 2 ) / 0.001 ) * -.5) set ASq22 exp ( ( (( climate4 - 0.22 ) ^ 2 ) / 0.001 ) * -.5) set ASq23 exp ( ( (( climate4 - 0.23 ) ^ 2 ) / 0.001 ) * -.5) set ASq24 exp ( ( (( climate4 - 0.24 ) ^ 2 ) / 0.001 ) * -.5) set ASq25 exp ( ( (( climate4 - 0.25 ) ^ 2 ) / 0.001 ) * -.5) set ASq26 exp ( ( (( climate4 - 0.26 ) ^ 2 ) / 0.001 ) * -.5) set ASq27 exp ( ( (( climate4 - 0.27 ) ^ 2 ) / 0.001 ) * -.5) set ASq28 exp ( ( (( climate4 - 0.28 ) ^ 2 ) / 0.001 ) * -.5) set ASq29 exp ( ( (( climate4 - 0.29 ) ^ 2 ) / 0.001 ) * -.5) set ASq30 exp ( ( (( climate4 - 0.39 ) ^ 2 ) / 0.001 ) * -.5) set ASq31 exp ( ( (( climate4 - 0.31 ) ^ 2 ) / 0.001 ) * -.5) set ASq32 exp ( ( (( climate4 - 0.32 ) ^ 2 ) / 0.001 ) * -.5) set ASq33 exp ( ( (( climate4 - 0.33 ) ^ 2 ) / 0.001 ) * -.5) set ASq34 exp ( ( (( climate4 - 0.34 ) ^ 2 ) / 0.001 ) * -.5) set ASq35 exp ( ( (( climate4 - 0.35 ) ^ 2 ) / 0.001 ) * -.5) set ASq36 exp ( ( (( climate4 - 0.36 ) ^ 2 ) / 0.001 ) * -.5) set ASq37 exp ( ( (( climate4 - 0.37 ) ^ 2 ) / 0.001 ) * -.5) set ASq38 exp ( ( (( climate4 - 0.38 ) ^ 2 ) / 0.001 ) * -.5) set ASq39 exp ( ( (( climate4 - 0.39 ) ^ 2 ) / 0.001 ) * -.5) set ASq40 exp ( ( (( climate4 - 0.40 ) ^ 2 ) / 0.001 ) * -.5) set ASq41 exp ( ( (( climate4 - 0.41 ) ^ 2 ) / 0.001 ) * -.5) set ASq42 exp ( ( (( climate4 - 0.42 ) ^ 2 ) / 0.001 ) * -.5) set ASq43 exp ( ( (( climate4 - 0.43 ) ^ 2 ) / 0.001 ) * -.5) set ASq44 exp ( ( (( climate4 - 0.44 ) ^ 2 ) / 0.001 ) * -.5) set ASq45 exp ( ( (( climate4 - 0.45 ) ^ 2 ) / 0.001 ) * -.5) set ASq46 exp ( ( (( climate4 - 0.46 ) ^ 2 ) / 0.001 ) * -.5) set ASq47 exp ( ( (( climate4 - 0.47 ) ^ 2 ) / 0.001 ) * -.5) set ASq48 exp ( ( (( climate4 - 0.48 ) ^ 2 ) / 0.001 ) * -.5 ) set ASq49 exp ( ( (( climate4 - 0.49 ) ^ 2 ) / 0.001 ) * -.5 ) set ASq50 exp ( ( (( climate4 - 0.5 ) ^ 2 ) / 0.001 ) * -.5 ) set ASq51 exp ( ( (( climate4 - 0.51 ) ^ 2 ) / 0.001 ) * -.5 ) set ASq52 exp ( ( (( climate4 - 0.52 ) ^ 2 ) / 0.001 ) * -.5 ) set ASq53 exp ( ( (( climate4 - 0.53 ) ^ 2 ) / 0.001 ) * -.5) set ASq54 exp ( ( (( climate4 - 0.54 ) ^ 2 ) / 0.001 ) * -.5) set ASq55 exp ( ( (( climate4 - 0.55 ) ^ 2 ) / 0.001 ) * -.5) set ASq56 exp ( ( (( climate4 - 0.56 ) ^ 2 ) / 0.001 ) * -.5) set ASq57 exp ( ( (( climate4 - 0.57 ) ^ 2 ) / 0.001 ) * -.5) set ASq58 exp ( ( (( climate4 - 0.58 ) ^ 2 ) / 0.001 ) * -.5) set ASq59 exp ( ( (( climate4 - 0.59 ) ^ 2 ) / 0.001 ) * -.5) set ASq60 exp ( ( (( climate4 - 0.60 ) ^ 2 ) / 0.001 ) * -.5) set ASq61 exp ( ( (( climate4 - 0.61 ) ^ 2 ) / 0.001 ) * -.5) set ASq62 exp ( ( (( climate4 - 0.62 ) ^ 2 ) / 0.001 ) * -.5) set ASq63 exp ( ( (( climate4 - 0.63 ) ^ 2 ) / 0.001 ) * -.5) set ASq64 exp ( ( (( climate4 - 0.64 ) ^ 2 ) / 0.001 ) * -.5) set ASq65 exp ( ( (( climate4 - 0.65 ) ^ 2 ) / 0.001 ) * -.5) set ASq66 exp ( ( (( climate4 - 0.66 ) ^ 2 ) / 0.001 ) * -.5) set ASq67 exp ( ( (( climate4 - 0.67 ) ^ 2 ) / 0.001 ) * -.5) set ASq68 exp ( ( (( climate4 - 0.68 ) ^ 2 ) / 0.001 ) * -.5) set ASq69 exp ( ( (( climate4 - 0.69 ) ^ 2 ) / 0.001 ) * -.5) set ASq70 exp ( ( (( climate4 - 0.70 ) ^ 2 ) / 0.001 ) * -.5) set ASq71 exp ( ( (( climate4 - 0.71 ) ^ 2 ) / 0.001 ) * -.5) set ASq72 exp ( ( (( climate4 - 0.72 ) ^ 2 ) / 0.001 ) * -.5) set ASq73 exp ( ( (( climate4 - 0.73 ) ^ 2 ) / 0.001 ) * -.5) set ASq74 exp ( ( (( climate4 - 0.74 ) ^ 2 ) / 0.001 ) * -.5) set ASq75 exp ( ( (( climate4 - 0.75 ) ^ 2 ) / 0.001 ) * -.5) set ASq76 exp ( ( (( climate4 - 0.76 ) ^ 2 ) / 0.001 ) * -.5) set ASq77 exp ( ( (( climate4 - 0.77 ) ^ 2 ) / 0.001 ) * -.5) set ASq78 exp ( ( (( climate4 - 0.78 ) ^ 2 ) / 0.001 ) * -.5) set ASq79 exp ( ( (( climate4 - 0.79 ) ^ 2 ) / 0.001 ) * -.5) set ASq80 exp ( ( (( climate4 - 0.80 ) ^ 2 ) / 0.001 ) * -.5) set ASq81 exp ( ( (( climate4 - 0.81 ) ^ 2 ) / 0.001 ) * -.5) set ASq82 exp ( ( (( climate4 - 0.82 ) ^ 2 ) / 0.001 ) * -.5) set ASq83 exp ( ( (( climate4 - 0.83 ) ^ 2 ) / 0.001 ) * -.5) set ASq84 exp ( ( (( climate4 - 0.84 ) ^ 2 ) / 0.001 ) * -.5) set ASq85 exp ( ( (( climate4 - 0.85 ) ^ 2 ) / 0.001 ) * -.5) set ASq86 exp ( ( (( climate4 - 0.86 ) ^ 2 ) / 0.001 ) * -.5) set ASq87 exp ( ( (( climate4 - 0.87 ) ^ 2 ) / 0.001 ) * -.5) set ASq88 exp ( ( (( climate4 - 0.88 ) ^ 2 ) / 0.001 ) * -.5) set ASq89 exp ( ( (( climate4 - 0.89 ) ^ 2 ) / 0.001 ) * -.5) set ASq90 exp ( ( (( climate4 - 0.9 ) ^ 2 ) / 0.001 ) * -.5) set ASq91 exp ( ( (( climate4 - 0.91 ) ^ 2 ) / 0.001 ) * -.5) set ASq92 exp ( ( (( climate4 - 0.92 ) ^ 2 ) / 0.001 ) * -.5) set ASq93 exp ( ( (( climate4 - 0.93 ) ^ 2 ) / 0.001 ) * -.5) set ASq94 exp ( ( (( climate4 - 0.94 ) ^ 2 ) / 0.001 ) * -.5) set ASq95 exp ( ( (( climate4 - 0.95 ) ^ 2 ) / 0.001 ) * -.5) set ASq96 exp ( ( (( climate4 - 0.96 ) ^ 2 ) / 0.001 ) * -.5) set ASq97 exp ( ( (( climate4 - 0.97 ) ^ 2 ) / 0.001 ) * -.5) set ASq98 exp ( ( (( climate4 - 0.98 ) ^ 2 ) / 0.001 ) * -.5) set ASq99 exp ( ( (( climate4 - 0.99 ) ^ 2 ) / 0.001 ) * -.5) set ASq100 exp ( ( (( climate4 - 1) ^ 2 ) / 0.001 ) * -.5) ] ; set counterQ count patches with [climate1 > 0 AND climate1 < 1] ; set HRange max [climate1] of patches - min [climate1] of patches ; set HVar standard-deviation [climate1] of patches with [clim ; ask patches [ ; set pcolor scale-color orange climate4 0 100 ; climate1 ; ] end ; THE ESTAB SUBROUTINE SPROUTS AN INDIVIDUAL OF A DISPERSAL LIMITED SPECIES ON A NEARBY PATCH ; IF IT HAS A SUITABLE CLIMATE. UBIQUITOUS DISPERSING SPECIES SPROUT EVERYWHERE IF ONE IS AT LEAST 6 YR OLD ; THESE NEW SEEDLINGS DIE AT A HIGH RATE BY CALLING A DEATH3 SUBROUTINE to estab random-seed seed + 150 set randyr 0.8 ask patches [ if (count turtles-here < limit) [ if (count Sp1s in-radius 3.19 > 0) [sprout-Sp1s 1 [set size 1 set deathv 1 set age 0 set color pink ]] if (count Sp3s in-radius 3.19 > 0) [sprout-Sp3s 1 [set size 1 set deathv 1 set age 0 set color pink ]] if (count Sp5s in-radius 3.19 > 0) [sprout-Sp5s 1 [set size 1 set deathv 1 set age 0 set color pink ]] if (count Sp7s in-radius 3.19 > 0) [sprout-Sp7s 1 [set size 1 set deathv 1 set age 0 set color pink ]] if (count Sp9s in-radius 3.19 > 0) [sprout-Sp9s 1 [set size 1 set deathv 1 set age 0 set color pink ]] if (count Sp11s in-radius 3.19 > 0) [sprout-Sp11s 1 [set size 1 set deathv 1 set age 0 set color pink ]] if (count Sp13s in-radius 3.19 > 0) [sprout-Sp13s 1 [set size 1 set deathv 1 set age 0 set color pink ]] if (count Sp15s in-radius 3.19 > 0) [sprout-Sp15s 1 [set size 1 set deathv 1 set age 0 set color pink ]] if (count Sp17s in-radius 3.19 > 0) [sprout-Sp17s 1 [set size 1 set deathv 1 set age 0 set color pink ]] if (count Sp19s in-radius 3.19 > 0) [sprout-Sp19s 1 [set size 1 set deathv 1 set age 0 set color pink ]] if (count Sp21s in-radius 3.19 > 0) [sprout-Sp21s 1 [set size 1 set deathv 1 set age 0 set color pink ]] if (count Sp23s in-radius 3.19 > 0) [sprout-Sp23s 1 [set size 1 set deathv 1 set age 0 set color pink ]] if (count Sp25s in-radius 3.19 > 0) [sprout-Sp25s 1 [set size 1 set deathv 1 set age 0 set color pink ]] if (count Sp27s in-radius 3.19 > 0) [sprout-Sp27s 1 [set size 1 set deathv 1 set age 0 set color pink ]] if (count Sp29s in-radius 3.19 > 0) [sprout-Sp29s 1 [set size 1 set deathv 1 set age 0 set color pink ]] if (count Sp31s in-radius 3.19 > 0) [sprout-Sp31s 1 [set size 1 set deathv 1 set age 0 set color pink ]] if (count Sp33s in-radius 3.19 > 0) [sprout-Sp33s 1 [set size 1 set deathv 1 set age 0 set color pink ]] if (count Sp35s in-radius 3.19 > 0) [sprout-Sp35s 1 [set size 1 set deathv 1 set age 0 set color pink ]] if (count Sp37s in-radius 3.19 > 0) [sprout-Sp37s 1 [set size 1 set deathv 1 set age 0 set color pink ]] if (count Sp39s in-radius 3.19 > 0) [sprout-Sp39s 1 [set size 1 set deathv 1 set age 0 set color pink ]] if (count Sp41s in-radius 3.19 > 0) [sprout-Sp41s 1 [set size 1 set deathv 1 set age 0 set color pink ]] if (count Sp43s in-radius 3.19 > 0) [sprout-Sp43s 1 [set size 1 set deathv 1 set age 0 set color pink ]] if (count Sp45s in-radius 3.19 > 0) [sprout-Sp45s 1 [set size 1 set deathv 1 set age 0 set color pink ]] if (count Sp47s in-radius 3.19 > 0) [sprout-Sp47s 1 [set size 1 set deathv 1 set age 0 set color pink ]] if (count Sp49s in-radius 3.19 > 0) [sprout-Sp49s 1 [set size 1 set deathv 1 set age 0 set color pink ]] if (count Sp51s in-radius 3.19 > 0) [sprout-Sp51s 1 [set size 1 set deathv 1 set age 0 set color pink ]] if (count Sp53s in-radius 3.19 > 0) [sprout-Sp53s 1 [set size 1 set deathv 1 set age 0 set color pink ]] if (count Sp55s in-radius 3.19 > 0) [sprout-Sp55s 1 [set size 1 set deathv 1 set age 0 set color pink ]] if (count Sp57s in-radius 3.19 > 0) [sprout-Sp57s 1 [set size 1 set deathv 1 set age 0 set color pink ]] if (count Sp59s in-radius 3.19 > 0) [sprout-Sp59s 1 [set size 1 set deathv 1 set age 0 set color pink ]] if (count Sp61s in-radius 3.19 > 0) [sprout-Sp61s 1 [set size 1 set deathv 1 set age 0 set color pink ]] if (count Sp63s in-radius 3.19 > 0) [sprout-Sp63s 1 [set size 1 set deathv 1 set age 0 set color pink ]] if (count Sp65s in-radius 3.19 > 0) [sprout-Sp65s 1 [set size 1 set deathv 1 set age 0 set color pink ]] if (count Sp67s in-radius 3.19 > 0) [sprout-Sp67s 1 [set size 1 set deathv 1 set age 0 set color pink ]] if (count Sp69s in-radius 3.19 > 0) [sprout-Sp69s 1 [set size 1 set deathv 1 set age 0 set color pink ]] if (count Sp71s in-radius 3.19 > 0) [sprout-Sp71s 1 [set size 1 set deathv 1 set age 0 set color pink ]] if (count Sp73s in-radius 3.19 > 0) [sprout-Sp73s 1 [set size 1 set deathv 1 set age 0 set color pink ]] if (count Sp75s in-radius 3.19 > 0) [sprout-Sp75s 1 [set size 1 set deathv 1 set age 0 set color pink ]] if (count Sp77s in-radius 3.19 > 0) [sprout-Sp77s 1 [set size 1 set deathv 1 set age 0 set color pink ]] if (count Sp79s in-radius 3.19 > 0) [sprout-Sp79s 1 [set size 1 set deathv 1 set age 0 set color pink ]] if (count Sp81s in-radius 3.19 > 0) [sprout-Sp81s 1 [set size 1 set deathv 1 set age 0 set color pink ]] if (count Sp83s in-radius 3.19 > 0) [sprout-Sp83s 1 [set size 1 set deathv 1 set age 0 set color pink ]] if (count Sp85s in-radius 3.19 > 0) [sprout-Sp85s 1 [set size 1 set deathv 1 set age 0 set color pink ]] if (count Sp87s in-radius 3.19 > 0) [sprout-Sp87s 1 [set size 1 set deathv 1 set age 0 set color pink ]] if (count Sp89s in-radius 3.19 > 0) [sprout-Sp78s 1 [set size 1 set deathv 1 set age 0 set color pink ]] if (count Sp91s in-radius 3.19 > 0) [sprout-Sp91s 1 [set size 1 set deathv 1 set age 0 set color pink ]] if (count Sp93s in-radius 3.19 > 0) [sprout-Sp93s 1 [set size 1 set deathv 1 set age 0 set color pink ]] if (count Sp95s in-radius 3.19 > 0) [sprout-Sp95s 1 [set size 1 set deathv 1 set age 0 set color pink ]] if (count Sp97s in-radius 3.19 > 0) [sprout-Sp97s 1 [set size 1 set deathv 1 set age 0 set color pink ]] if (count Sp99s in-radius 3.19 > 0) [sprout-Sp99s 1 [set size 1 set deathv 1 set age 0 set color pink ]] if ( count Sp100s with [age > 6] > 0 AND random-float 1 > randyr ) [ sprout-Sp100s 1 [ set size 1 set deathv 1 set age 0 set color pink ]] if ( count Sp10s with [age > 6] > 0 AND random-float 1 > randyr ) [ sprout-Sp10s 1 [ set size 1 set deathv 1 set age 0 set color pink ]] if ( count Sp12s with [age > 6] > 0 AND random-float 1 > randyr ) [ sprout-Sp12s 1 [ set size 1 set deathv 1 set age 0 set color pink ]] if ( count Sp14s with [age > 6] > 0 AND random-float 1 > randyr ) [ sprout-Sp14s 1 [ set size 1 set deathv 1 set age 0 set color pink ]] if ( count Sp16s with [age > 6] > 0 AND random-float 1 > randyr ) [ sprout-Sp16s 1 [ set size 1 set deathv 1 set age 0 set color pink ]] if ( count Sp18s with [age > 6] > 0 AND random-float 1 > randyr ) [ sprout-Sp18s 1 [ set size 1 set deathv 1 set age 0 set color pink ]] if ( count Sp20s with [age > 6] > 0 AND random-float 1 > randyr ) [ sprout-Sp20s 1 [ set size 1 set deathv 1 set age 0 set color pink ]] if ( count Sp22s with [age > 6] > 0 AND random-float 1 > randyr ) [ sprout-Sp22s 1 [ set size 1 set deathv 1 set age 0 set color pink ]] if ( count Sp24s with [age > 6] > 0 AND random-float 1 > randyr ) [ sprout-Sp24s 1 [ set size 1 set deathv 1 set age 0 set color pink ]] if ( count Sp26s with [age > 6] > 0 AND random-float 1 > randyr ) [ sprout-Sp26s 1 [ set size 1 set deathv 1 set age 0 set color pink ]] if ( count Sp28s with [age > 6] > 0 AND random-float 1 > randyr ) [ sprout-Sp28s 1 [ set size 1 set deathv 1 set age 0 set color pink ]] if ( count Sp2s with [age > 6] > 0 AND random-float 1 > randyr ) [ sprout-Sp2s 1 [ set size 1 set deathv 1 set age 0 set color pink ]] if ( count Sp30s with [age > 6] > 0 AND random-float 1 > randyr ) [ sprout-Sp30s 1 [ set size 1 set deathv 1 set age 0 set color pink ]] if ( count Sp32s with [age > 6] > 0 AND random-float 1 > randyr ) [ sprout-Sp32s 1 [ set size 1 set deathv 1 set age 0 set color pink ]] if ( count Sp34s with [age > 6] > 0 AND random-float 1 > randyr ) [ sprout-Sp34s 1 [ set size 1 set deathv 1 set age 0 set color pink ]] if ( count Sp36s with [age > 6] > 0 AND random-float 1 > randyr ) [ sprout-Sp36s 1 [ set size 1 set deathv 1 set age 0 set color pink ]] if ( count Sp38s with [age > 6] > 0 AND random-float 1 > randyr ) [ sprout-Sp38s 1 [ set size 1 set deathv 1 set age 0 set color pink ]] if ( count Sp40s with [age > 6] > 0 AND random-float 1 > randyr ) [ sprout-Sp40s 1 [ set size 1 set deathv 1 set age 0 set color pink ]] if ( count Sp42s with [age > 6] > 0 AND random-float 1 > randyr ) [ sprout-Sp42s 1 [ set size 1 set deathv 1 set age 0 set color pink ]] if ( count Sp44s with [age > 6] > 0 AND random-float 1 > randyr ) [ sprout-Sp44s 1 [ set size 1 set deathv 1 set age 0 set color pink ]] if ( count Sp46s with [age > 6] > 0 AND random-float 1 > randyr ) [ sprout-Sp46s 1 [ set size 1 set deathv 1 set age 0 set color pink ]] if ( count Sp48s with [age > 6] > 0 AND random-float 1 > randyr ) [ sprout-Sp48s 1 [ set size 1 set deathv 1 set age 0 set color pink ]] if ( count Sp4s with [age > 6] > 0 AND random-float 1 > randyr ) [ sprout-Sp4s 1 [ set size 1 set deathv 1 set age 0 set color pink ]] if ( count Sp50s with [age > 6] > 0 AND random-float 1 > randyr ) [ sprout-Sp50s 1 [ set size 1 set deathv 1 set age 0 set color pink ]] if ( count Sp52s with [age > 6] > 0 AND random-float 1 > randyr ) [ sprout-Sp52s 1 [ set size 1 set deathv 1 set age 0 set color pink ]] if ( count Sp54s with [age > 6] > 0 AND random-float 1 > randyr ) [ sprout-Sp54s 1 [ set size 1 set deathv 1 set age 0 set color pink ]] if ( count Sp56s with [age > 6] > 0 AND random-float 1 > randyr ) [ sprout-Sp56s 1 [ set size 1 set deathv 1 set age 0 set color pink ]] if ( count Sp58s with [age > 6] > 0 AND random-float 1 > randyr ) [ sprout-Sp58s 1 [ set size 1 set deathv 1 set age 0 set color pink ]] if ( count Sp60s with [age > 6] > 0 AND random-float 1 > randyr ) [ sprout-Sp60s 1 [ set size 1 set deathv 1 set age 0 set color pink ]] if ( count Sp62s with [age > 6] > 0 AND random-float 1 > randyr ) [ sprout-Sp62s 1 [ set size 1 set deathv 1 set age 0 set color pink ]] if ( count Sp64s with [age > 6] > 0 AND random-float 1 > randyr ) [ sprout-Sp64s 1 [ set size 1 set deathv 1 set age 0 set color pink ]] if ( count Sp66s with [age > 6] > 0 AND random-float 1 > randyr ) [ sprout-Sp66s 1 [ set size 1 set deathv 1 set age 0 set color pink ]] if ( count Sp68s with [age > 6] > 0 AND random-float 1 > randyr ) [ sprout-Sp68s 1 [ set size 1 set deathv 1 set age 0 set color pink ]] if ( count Sp6s with [age > 6] > 0 AND random-float 1 > randyr ) [ sprout-Sp6s 1 [ set size 1 set deathv 1 set age 0 set color pink ]] if ( count Sp70s with [age > 6] > 0 AND random-float 1 > randyr ) [ sprout-Sp70s 1 [ set size 1 set deathv 1 set age 0 set color pink ]] if ( count Sp72s with [age > 6] > 0 AND random-float 1 > randyr ) [ sprout-Sp72s 1 [ set size 1 set deathv 1 set age 0 set color pink ]] if ( count Sp74s with [age > 6] > 0 AND random-float 1 > randyr ) [ sprout-Sp74s 1 [ set size 1 set deathv 1 set age 0 set color pink ]] if ( count Sp76s with [age > 6] > 0 AND random-float 1 > randyr ) [ sprout-Sp76s 1 [ set size 1 set deathv 1 set age 0 set color pink ]] if ( count Sp78s with [age > 6] > 0 AND random-float 1 > randyr ) [ sprout-Sp78s 1 [ set size 1 set deathv 1 set age 0 set color pink ]] if ( count Sp80s with [age > 6] > 0 AND random-float 1 > randyr ) [ sprout-Sp80s 1 [ set size 1 set deathv 1 set age 0 set color pink ]] if ( count Sp82s with [age > 6] > 0 AND random-float 1 > randyr ) [ sprout-Sp82s 1 [ set size 1 set deathv 1 set age 0 set color pink ]] if ( count Sp84s with [age > 6] > 0 AND random-float 1 > randyr ) [ sprout-Sp84s 1 [ set size 1 set deathv 1 set age 0 set color pink ]] if ( count Sp86s with [age > 6] > 0 AND random-float 1 > randyr ) [ sprout-Sp86s 1 [ set size 1 set deathv 1 set age 0 set color pink ]] if ( count Sp88s with [age > 6] > 0 AND random-float 1 > randyr ) [ sprout-Sp88s 1 [ set size 1 set deathv 1 set age 0 set color pink ]] if ( count Sp8s with [age > 6] > 0 AND random-float 1 > randyr ) [ sprout-Sp8s 1 [ set size 1 set deathv 1 set age 0 set color pink ]] if ( count Sp90s with [age > 6] > 0 AND random-float 1 > randyr ) [ sprout-Sp90s 1 [ set size 1 set deathv 1 set age 0 set color pink ]] if ( count Sp92s with [age > 6] > 0 AND random-float 1 > randyr ) [ sprout-Sp92s 1 [ set size 1 set deathv 1 set age 0 set color pink ]] if ( count Sp94s with [age > 6] > 0 AND random-float 1 > randyr ) [ sprout-Sp94s 1 [ set size 1 set deathv 1 set age 0 set color pink ]] if ( count Sp96s with [age > 6] > 0 AND random-float 1 > randyr ) [ sprout-Sp96s 1 [ set size 1 set deathv 1 set age 0 set color pink ]] if ( count Sp98s with [age > 6] > 0 AND random-float 1 > randyr ) [ sprout-Sp98s 1 [ set size 1 set deathv 1 set age 0 set color pink ]] ] ] death3 end ; THE DEATH SUBROUTINE KILLS INDIVIDUALS OF AGE > 2, WITH A HIGHER RATE FOR UBIQUITOUS DISPERSING SPECIES to death random-seed seed + 200 set counterDie10 0 ask Sp1s [ if ( age > 2 AND ASQD1 < random-float 0.079999 ) [ set counterdie10 counterdie10 + 1 die] ] ask Sp2s [ if ( age > 2 AND ASQD2 < random-float 0.019999 ) [ set counterdie10 counterdie10 + 1 die] ] ask Sp3s [ if ( age > 2 AND ASQD3 < random-float 0.079999 ) [ set counterdie10 counterdie10 + 1 die] ] ask Sp4s [ if ( age > 2 AND ASQD4 < random-float 0.019999 ) [ set counterdie10 counterdie10 + 1 die] ] ask Sp5s [ if ( age > 2 AND ASQD5 < random-float 0.079999 ) [ set counterdie10 counterdie10 + 1 die] ] ask Sp6s [ if ( age > 2 AND ASQD6 < random-float 0.019999 ) [ set counterdie10 counterdie10 + 1 die] ] ask Sp7s [ if ( age > 2 AND ASQD7 < random-float 0.079999 ) [ set counterdie10 counterdie10 + 1 die] ] ask Sp8s [ if ( age > 2 AND ASQD8 < random-float 0.019999 ) [ set counterdie10 counterdie10 + 1 die] ] ask Sp9s [ if ( age > 2 AND ASQD9 < random-float 0.079999 ) [ set counterdie10 counterdie10 + 1 die] ] ask Sp10s [ if ( age > 2 AND ASQD10 < random-float 0.019999 ) [ set counterdie10 counterdie10 + 1 die] ] ask Sp11s [ if ( age > 2 AND ASQD11 < random-float 0.079999 ) [ set counterdie10 counterdie10 + 1 die] ] ask Sp12s [ if ( age > 2 AND ASQD12 < random-float 0.019999 ) [ set counterdie10 counterdie10 + 1 die] ] ask Sp13s [ if ( age > 2 AND ASQD13 < random-float 0.079999 ) [ set counterdie10 counterdie10 + 1 die] ] ask Sp14s [ if ( age > 2 AND ASQD14 < random-float 0.019999 ) [ set counterdie10 counterdie10 + 1 die] ] ask Sp15s [ if ( age > 2 AND ASQD15 < random-float 0.079999 ) [ set counterdie10 counterdie10 + 1 die] ] ask Sp16s [ if ( age > 2 AND ASQD16 < random-float 0.019999 ) [ set counterdie10 counterdie10 + 1 die] ] ask Sp17s [ if ( age > 2 AND ASQD17 < random-float 0.079999 ) [ set counterdie10 counterdie10 + 1 die] ] ask Sp18s [ if ( age > 2 AND ASQD18 < random-float 0.019999 ) [ set counterdie10 counterdie10 + 1 die] ] ask Sp19s [ if ( age > 2 AND ASQD19 < random-float 0.079999 ) [ set counterdie10 counterdie10 + 1 die] ] ask Sp20s [ if ( age > 2 AND ASQD20 < random-float 0.019999 ) [ set counterdie10 counterdie10 + 1 die] ] ask Sp21s [ if ( age > 2 AND ASQD21 < random-float 0.079999 ) [ set counterdie10 counterdie10 + 1 die] ] ask Sp22s [ if ( age > 2 AND ASQD22 < random-float 0.019999 ) [ set counterdie10 counterdie10 + 1 die] ] ask Sp23s [ if ( age > 2 AND ASQD23 < random-float 0.079999 ) [ set counterdie10 counterdie10 + 1 die] ] ask Sp24s [ if ( age > 2 AND ASQD24 < random-float 0.019999 ) [ set counterdie10 counterdie10 + 1 die] ] ask Sp25s [ if ( age > 2 AND ASQD25 < random-float 0.079999 ) [ set counterdie10 counterdie10 + 1 die] ] ask Sp26s [ if ( age > 2 AND ASQD26 < random-float 0.019999 ) [ set counterdie10 counterdie10 + 1 die] ] ask Sp27s [ if ( age > 2 AND ASQD27 < random-float 0.079999 ) [ set counterdie10 counterdie10 + 1 die] ] ask Sp28s [ if ( age > 2 AND ASQD28 < random-float 0.019999 ) [ set counterdie10 counterdie10 + 1 die] ] ask Sp29s [ if ( age > 2 AND ASQD29 < random-float 0.079999 ) [ set counterdie10 counterdie10 + 1 die] ] ask Sp30s [ if ( age > 2 AND ASQD30 < random-float 0.019999 ) [ set counterdie10 counterdie10 + 1 die] ] ask Sp31s [ if ( age > 2 AND ASQD31 < random-float 0.079999 ) [ set counterdie10 counterdie10 + 1 die] ] ask Sp32s [ if ( age > 2 AND ASQD32 < random-float 0.019999 ) [ set counterdie10 counterdie10 + 1 die] ] ask Sp33s [ if ( age > 2 AND ASQD33 < random-float 0.079999 ) [ set counterdie10 counterdie10 + 1 die] ] ask Sp34s [ if ( age > 2 AND ASQD34 < random-float 0.019999 ) [ set counterdie10 counterdie10 + 1 die] ] ask Sp35s [ if ( age > 2 AND ASQD35 < random-float 0.079999 ) [ set counterdie10 counterdie10 + 1 die] ] ask Sp36s [ if ( age > 2 AND ASQD36 < random-float 0.019999 ) [ set counterdie10 counterdie10 + 1 die] ] ask Sp37s [ if ( age > 2 AND ASQD37 < random-float 0.079999 ) [ set counterdie10 counterdie10 + 1 die] ] ask Sp38s [ if ( age > 2 AND ASQD38 < random-float 0.019999 ) [ set counterdie10 counterdie10 + 1 die] ] ask Sp39s [ if ( age > 2 AND ASQD39 < random-float 0.079999 ) [ set counterdie10 counterdie10 + 1 die] ] ask Sp40s [ if ( age > 2 AND ASQD40 < random-float 0.019999 ) [ set counterdie10 counterdie10 + 1 die] ] ask Sp41s [ if ( age > 2 AND ASQD41 < random-float 0.079999 ) [ set counterdie10 counterdie10 + 1 die] ] ask Sp42s [ if ( age > 2 AND ASQD42 < random-float 0.019999 ) [ set counterdie10 counterdie10 + 1 die] ] ask Sp43s [ if ( age > 2 AND ASQD43 < random-float 0.079999 ) [ set counterdie10 counterdie10 + 1 die] ] ask Sp44s [ if ( age > 2 AND ASQD44 < random-float 0.019999 ) [ set counterdie10 counterdie10 + 1 die] ] ask Sp45s [ if ( age > 2 AND ASQD45 < random-float 0.079999 ) [ set counterdie10 counterdie10 + 1 die] ] ask Sp46s [ if ( age > 2 AND ASQD46 < random-float 0.019999 ) [ set counterdie10 counterdie10 + 1 die] ] ask Sp47s [ if ( age > 2 AND ASQD47 < random-float 0.079999 ) [ set counterdie10 counterdie10 + 1 die] ] ask Sp48s [ if ( age > 2 AND ASQD48 < random-float 0.019999 ) [ set counterdie10 counterdie10 + 1 die] ] ask Sp49s [ if ( age > 2 AND ASQD49 < random-float 0.079999 ) [ set counterdie10 counterdie10 + 1 die] ] ask Sp50s [ if ( age > 2 AND ASQD50 < random-float 0.019999 ) [ set counterdie10 counterdie10 + 1 die] ] ask Sp51s [ if ( age > 2 AND ASQD51 < random-float 0.079999 ) [ set counterdie10 counterdie10 + 1 die] ] ask Sp52s [ if ( age > 2 AND ASQD52 < random-float 0.019999 ) [ set counterdie10 counterdie10 + 1 die] ] ask Sp53s [ if ( age > 2 AND ASQD53 < random-float 0.079999 ) [ set counterdie10 counterdie10 + 1 die] ] ask Sp54s [ if ( age > 2 AND ASQD54 < random-float 0.019999 ) [ set counterdie10 counterdie10 + 1 die] ] ask Sp55s [ if ( age > 2 AND ASQD55 < random-float 0.079999 ) [ set counterdie10 counterdie10 + 1 die] ] ask Sp56s [ if ( age > 2 AND ASQD56 < random-float 0.019999 ) [ set counterdie10 counterdie10 + 1 die] ] ask Sp57s [ if ( age > 2 AND ASQD57 < random-float 0.079999 ) [ set counterdie10 counterdie10 + 1 die] ] ask Sp58s [ if ( age > 2 AND ASQD58 < random-float 0.019999 ) [ set counterdie10 counterdie10 + 1 die] ] ask Sp59s [ if ( age > 2 AND ASQD59 < random-float 0.079999 ) [ set counterdie10 counterdie10 + 1 die] ] ask Sp60s [ if ( age > 2 AND ASQD60 < random-float 0.019999 ) [ set counterdie10 counterdie10 + 1 die] ] ask Sp61s [ if ( age > 2 AND ASQD61 < random-float 0.079999 ) [ set counterdie10 counterdie10 + 1 die] ] ask Sp62s [ if ( age > 2 AND ASQD62 < random-float 0.019999 ) [ set counterdie10 counterdie10 + 1 die] ] ask Sp63s [ if ( age > 2 AND ASQD63 < random-float 0.079999 ) [ set counterdie10 counterdie10 + 1 die] ] ask Sp64s [ if ( age > 2 AND ASQD64 < random-float 0.019999 ) [ set counterdie10 counterdie10 + 1 die] ] ask Sp65s [ if ( age > 2 AND ASQD65 < random-float 0.079999 ) [ set counterdie10 counterdie10 + 1 die] ] ask Sp66s [ if ( age > 2 AND ASQD66 < random-float 0.019999 ) [ set counterdie10 counterdie10 + 1 die] ] ask Sp67s [ if ( age > 2 AND ASQD67 < random-float 0.079999 ) [ set counterdie10 counterdie10 + 1 die] ] ask Sp68s [ if ( age > 2 AND ASQD68 < random-float 0.019999 ) [ set counterdie10 counterdie10 + 1 die] ] ask Sp69s [ if ( age > 2 AND ASQD69 < random-float 0.079999 ) [ set counterdie10 counterdie10 + 1 die] ] ask Sp70s [ if ( age > 2 AND ASQD70 < random-float 0.019999 ) [ set counterdie10 counterdie10 + 1 die] ] ask Sp71s [ if ( age > 2 AND ASQD71 < random-float 0.079999 ) [ set counterdie10 counterdie10 + 1 die] ] ask Sp72s [ if ( age > 2 AND ASQD72 < random-float 0.019999 ) [ set counterdie10 counterdie10 + 1 die] ] ask Sp73s [ if ( age > 2 AND ASQD73 < random-float 0.079999 ) [ set counterdie10 counterdie10 + 1 die] ] ask Sp74s [ if ( age > 2 AND ASQD74 < random-float 0.019999 ) [ set counterdie10 counterdie10 + 1 die] ] ask Sp75s [ if ( age > 2 AND ASQD75 < random-float 0.079999 ) [ set counterdie10 counterdie10 + 1 die] ] ask Sp76s [ if ( age > 2 AND ASQD76 < random-float 0.019999 ) [ set counterdie10 counterdie10 + 1 die] ] ask Sp77s [ if ( age > 2 AND ASQD77 < random-float 0.079999 ) [ set counterdie10 counterdie10 + 1 die] ] ask Sp78s [ if ( age > 2 AND ASQD78 < random-float 0.019999 ) [ set counterdie10 counterdie10 + 1 die] ] ask Sp79s [ if ( age > 2 AND ASQD79 < random-float 0.079999 ) [ set counterdie10 counterdie10 + 1 die] ] ask Sp80s [ if ( age > 2 AND ASQD80 < random-float 0.019999 ) [ set counterdie10 counterdie10 + 1 die] ] ask Sp81s [ if ( age > 2 AND ASQD81 < random-float 0.079999 ) [ set counterdie10 counterdie10 + 1 die] ] ask Sp82s [ if ( age > 2 AND ASQD82 < random-float 0.019999 ) [ set counterdie10 counterdie10 + 1 die] ] ask Sp83s [ if ( age > 2 AND ASQD83 < random-float 0.079999 ) [ set counterdie10 counterdie10 + 1 die] ] ask Sp84s [ if ( age > 2 AND ASQD84 < random-float 0.019999 ) [ set counterdie10 counterdie10 + 1 die] ] ask Sp85s [ if ( age > 2 AND ASQD85 < random-float 0.079999 ) [ set counterdie10 counterdie10 + 1 die] ] ask Sp86s [ if ( age > 2 AND ASQD86 < random-float 0.019999 ) [ set counterdie10 counterdie10 + 1 die] ] ask Sp87s [ if ( age > 2 AND ASQD87 < random-float 0.079999 ) [ set counterdie10 counterdie10 + 1 die] ] ask Sp88s [ if ( age > 2 AND ASQD88 < random-float 0.019999 ) [ set counterdie10 counterdie10 + 1 die] ] ask Sp89s [ if ( age > 2 AND ASQD89 < random-float 0.079999 ) [ set counterdie10 counterdie10 + 1 die] ] ask Sp90s [ if ( age > 2 AND ASQD90 < random-float 0.019999 ) [ set counterdie10 counterdie10 + 1 die] ] ask Sp91s [ if ( age > 2 AND ASQD91 < random-float 0.079999 ) [ set counterdie10 counterdie10 + 1 die] ] ask Sp92s [ if ( age > 2 AND ASQD92 < random-float 0.019999 ) [ set counterdie10 counterdie10 + 1 die] ] ask Sp93s [ if ( age > 2 AND ASQD93 < random-float 0.079999 ) [ set counterdie10 counterdie10 + 1 die] ] ask Sp94s [ if ( age > 2 AND ASQD94 < random-float 0.019999 ) [ set counterdie10 counterdie10 + 1 die] ] ask Sp95s [ if ( age > 2 AND ASQD95 < random-float 0.079999 ) [ set counterdie10 counterdie10 + 1 die] ] ask Sp96s [ if ( age > 2 AND ASQD96 < random-float 0.019999 ) [ set counterdie10 counterdie10 + 1 die] ] ask Sp97s [ if ( age > 2 AND ASQD97 < random-float 0.079999 ) [ set counterdie10 counterdie10 + 1 die] ] ask Sp98s [ if ( age > 2 AND ASQD98 < random-float 0.019999 ) [ set counterdie10 counterdie10 + 1 die] ] ask Sp99s [ if ( age > 2 AND ASQD99 < random-float 0.079999 ) [ set counterdie10 counterdie10 + 1 die] ] ask Sp100s [ if ( age > 2 AND ASQD100 < random-float 0.019999 ) [ set counterdie10 counterdie10 + 1 ] ] end ; THE DEATH3 SUBROUTINE KILLS THE NEWEST SEEDLINGS to death3 random-seed seed + 250 ask Sp1s [ if ( age < 3 AND ASQR1 < random-float 0.3 AND deathv = 1 ) [ die] ] ask Sp2s [ if ( age < 3 AND ASQR2 < random-float 0.2 AND deathv = 1 ) [ die] ] ask Sp3s [ if ( age < 3 AND ASQR3 < random-float 0.3 AND deathv = 1 ) [ die] ] ask Sp4s [ if ( age < 3 AND ASQR4 < random-float 0.2 AND deathv = 1 ) [ die] ] ask Sp5s [ if ( age < 3 AND ASQR5 < random-float 0.3 AND deathv = 1 ) [ die] ] ask Sp6s [ if ( age < 3 AND ASQR6 < random-float 0.2 AND deathv = 1 ) [die] ] ask Sp7s [ if ( age < 3 AND ASQR7 < random-float 0.3 AND deathv = 1 ) [ die] ] ask Sp8s [ if ( age < 3 AND ASQR8 < random-float 0.2 AND deathv = 1 ) [ die] ] ask Sp9s [ if ( age < 3 AND ASQR9 < random-float 0.3 AND deathv = 1 ) [ die] ] ask Sp10s [ if ( age < 3 AND ASQR10 < random-float 0.2 AND deathv = 1 ) [ die] ] ask Sp11s [ if ( age < 3 AND ASQR11 < random-float 0.3 AND deathv = 1 ) [ die] ] ask Sp12s [ if ( age < 3 AND ASQR12 < random-float 0.2 AND deathv = 1 ) [ die] ] ask Sp13s [ if ( age < 3 AND ASQR13 < random-float 0.3 AND deathv = 1 ) [ die] ] ask Sp14s [ if ( age < 3 AND ASQR14 < random-float 0.2 AND deathv = 1 ) [ die] ] ask Sp15s [ if ( age < 3 AND ASQR15 < random-float 0.3 AND deathv = 1 ) [ die] ] ask Sp16s [ if ( age < 3 AND ASQR16 < random-float 0.2 AND deathv = 1 ) [ die] ] ask Sp17s [ if ( age < 3 AND ASQR17 < random-float 0.3 AND deathv = 1 ) [ die] ] ask Sp18s [ if ( age < 3 AND ASQR18 < random-float 0.2 AND deathv = 1 ) [ die] ] ask Sp19s [ if ( age < 3 AND ASQR19 < random-float 0.3 AND deathv = 1 ) [ die] ] ask Sp20s [ if ( age < 3 AND ASQR20 < random-float 0.2 AND deathv = 1 ) [ die] ] ask Sp21s [ if ( age < 3 AND ASQR21 < random-float 0.3 AND deathv = 1 ) [ die] ] ask Sp22s [ if ( age < 3 AND ASQR22 < random-float 0.2 AND deathv = 1 ) [ die] ] ask Sp23s [ if ( age < 3 AND ASQR23 < random-float 0.3 AND deathv = 1 ) [ die] ] ask Sp24s [ if ( age < 3 AND ASQR24 < random-float 0.2 AND deathv = 1 ) [ die] ] ask Sp25s [ if ( age < 3 AND ASQR25 < random-float 0.3 AND deathv = 1 ) [ die] ] ask Sp26s [ if ( age < 3 AND ASQR26 < random-float 0.2 AND deathv = 1 ) [ die] ] ask Sp27s [ if ( age < 3 AND ASQR27 < random-float 0.3 AND deathv = 1 ) [ die] ] ask Sp28s [ if ( age < 3 AND ASQR28 < random-float 0.2 AND deathv = 1 ) [ die] ] ask Sp29s [ if ( age < 3 AND ASQR29 < random-float 0.3 AND deathv = 1 ) [ die] ] ask Sp30s [ if ( age < 3 AND ASQR30 < random-float 0.2 AND deathv = 1 ) [ die] ] ask Sp31s [ if ( age < 3 AND ASQR31 < random-float 0.3 AND deathv = 1 ) [ die] ] ask Sp32s [ if ( age < 3 AND ASQR32 < random-float 0.2 AND deathv = 1 ) [ die] ] ask Sp33s [ if ( age < 3 AND ASQR33 < random-float 0.3 AND deathv = 1 ) [ die] ] ask Sp34s [ if ( age < 3 AND ASQR34 < random-float 0.2 AND deathv = 1 ) [ die] ] ask Sp35s [ if ( age < 3 AND ASQR35 < random-float 0.3 AND deathv = 1 ) [ die] ] ask Sp36s [ if ( age < 3 AND ASQR36 < random-float 0.2 AND deathv = 1 ) [ die] ] ask Sp37s [ if ( age < 3 AND ASQR37 < random-float 0.3 AND deathv = 1 ) [ die] ] ask Sp38s [ if ( age < 3 AND ASQR38 < random-float 0.2 AND deathv = 1 ) [ die] ] ask Sp39s [ if ( age < 3 AND ASQR39 < random-float 0.3 AND deathv = 1 ) [ die] ] ask Sp40s [ if ( age < 3 AND ASQR40 < random-float 0.2 AND deathv = 1 ) [ die] ] ask Sp41s [ if ( age < 3 AND ASQR41 < random-float 0.3 AND deathv = 1 ) [ die] ] ask Sp42s [ if ( age < 3 AND ASQR42 < random-float 0.2 AND deathv = 1 ) [ die] ] ask Sp43s [ if ( age < 3 AND ASQR43 < random-float 0.3 AND deathv = 1 ) [ die] ] ask Sp44s [ if ( age < 3 AND ASQR44 < random-float 0.2 AND deathv = 1 ) [ die] ] ask Sp45s [ if ( age < 3 AND ASQR45 < random-float 0.3 AND deathv = 1 ) [ die] ] ask Sp46s [ if ( age < 3 AND ASQR46 < random-float 0.2 AND deathv = 1 ) [ die] ] ask Sp47s [ if ( age < 3 AND ASQR47 < random-float 0.3 AND deathv = 1 ) [ die] ] ask Sp48s [ if ( age < 3 AND ASQR48 < random-float 0.2 AND deathv = 1 ) [ die] ] ask Sp49s [ if ( age < 3 AND ASQR49 < random-float 0.3 AND deathv = 1 ) [ die] ] ask Sp50s [ if ( age < 3 AND ASQR50 < random-float 0.2 AND deathv = 1 ) [ die] ] ask Sp51s [ if ( age < 3 AND ASQR51 < random-float 0.3 AND deathv = 1 ) [ die] ] ask Sp52s [ if ( age < 3 AND ASQR52 < random-float 0.2 AND deathv = 1 ) [ die] ] ask Sp53s [ if ( age < 3 AND ASQR53 < random-float 0.3 AND deathv = 1 ) [ die] ] ask Sp54s [ if ( age < 3 AND ASQR54 < random-float 0.2 AND deathv = 1 ) [ die] ] ask Sp55s [ if ( age < 3 AND ASQR55 < random-float 0.3 AND deathv = 1 ) [ die] ] ask Sp56s [ if ( age < 3 AND ASQR56 < random-float 0.2 AND deathv = 1 ) [ die] ] ask Sp57s [ if ( age < 3 AND ASQR57 < random-float 0.2 AND deathv = 1 ) [ die] ] ask Sp58s [ if ( age < 3 AND ASQR58 < random-float 0.3 AND deathv = 1 ) [ die] ] ask Sp59s [ if ( age < 3 AND ASQR59 < random-float 0.2 AND deathv = 1 ) [ die] ] ask Sp60s [ if ( age < 3 AND ASQR60 < random-float 0.3 AND deathv = 1 ) [ die] ] ask Sp61s [ if ( age < 3 AND ASQR61 < random-float 0.2 AND deathv = 1 ) [ die] ] ask Sp62s [ if ( age < 3 AND ASQR62 < random-float 0.3 AND deathv = 1 ) [ die] ] ask Sp63s [ if ( age < 3 AND ASQR63 < random-float 0.2 AND deathv = 1 ) [ die] ] ask Sp64s [ if ( age < 3 AND ASQR64 < random-float 0.3 AND deathv = 1 ) [ die] ] ask Sp65s [ if ( age < 3 AND ASQR65 < random-float 0.2 AND deathv = 1 ) [ die] ] ask Sp66s [ if ( age < 3 AND ASQR66 < random-float 0.3 AND deathv = 1 ) [ die] ] ask Sp67s [ if ( age < 3 AND ASQR67 < random-float 0.2 AND deathv = 1 ) [ die] ] ask Sp68s [ if ( age < 3 AND ASQR68 < random-float 0.3 AND deathv = 1 ) [ die] ] ask Sp69s [ if ( age < 3 AND ASQR69 < random-float 0.2 AND deathv = 1 ) [ die] ] ask Sp70s [ if ( age < 3 AND ASQR70 < random-float 0.3 AND deathv = 1 ) [ die] ] ask Sp71s [ if ( age < 3 AND ASQR71 < random-float 0.2 AND deathv = 1 ) [ die] ] ask Sp72s [ if ( age < 3 AND ASQR72 < random-float 0.3 AND deathv = 1 ) [ die] ] ask Sp73s [ if ( age < 3 AND ASQR73 < random-float 0.2 AND deathv = 1 ) [ die] ] ask Sp74s [ if ( age < 3 AND ASQR74 < random-float 0.3 AND deathv = 1 ) [ die] ] ask Sp75s [ if ( age < 3 AND ASQR75 < random-float 0.2 AND deathv = 1 ) [ die] ] ask Sp76s [ if ( age < 3 AND ASQR76 < random-float 0.3 AND deathv = 1 ) [ die] ] ask Sp77s [ if ( age < 3 AND ASQR77 < random-float 0.2 AND deathv = 1 ) [ die] ] ask Sp78s [ if ( age < 3 AND ASQR78 < random-float 0.3 AND deathv = 1 ) [ die] ] ask Sp79s [ if ( age < 3 AND ASQR79 < random-float 0.2 AND deathv = 1 ) [ die] ] ask Sp80s [ if ( age < 3 AND ASQR80 < random-float 0.3 AND deathv = 1 ) [ die] ] ask Sp81s [ if ( age < 3 AND ASQR81 < random-float 0.2 AND deathv = 1 ) [ die] ] ask Sp82s [ if ( age < 3 AND ASQR82 < random-float 0.3 AND deathv = 1 ) [ die] ] ask Sp83s [ if ( age < 3 AND ASQR83 < random-float 0.2 AND deathv = 1 ) [ die] ] ask Sp84s [ if ( age < 3 AND ASQR84 < random-float 0.3 AND deathv = 1 ) [ die] ] ask Sp85s [ if ( age < 3 AND ASQR85 < random-float 0.2 AND deathv = 1 ) [ die] ] ask Sp86s [ if ( age < 3 AND ASQR86 < random-float 0.3 AND deathv = 1 ) [ die] ] ask Sp87s [ if ( age < 3 AND ASQR87 < random-float 0.2 AND deathv = 1 ) [ die] ] ask Sp88s [ if ( age < 3 AND ASQR88 < random-float 0.3 AND deathv = 1 ) [ die] ] ask Sp89s [ if ( age < 3 AND ASQR89 < random-float 0.2 AND deathv = 1 ) [ die] ] ask Sp90s [ if ( age < 3 AND ASQR90 < random-float 0.3 AND deathv = 1 ) [ die] ] ask Sp91s [ if ( age < 3 AND ASQR91 < random-float 0.2 AND deathv = 1 ) [ die] ] ask Sp92s [ if ( age < 3 AND ASQR92 < random-float 0.3 AND deathv = 1 ) [ die] ] ask Sp93s [ if ( age < 3 AND ASQR93 < random-float 0.3 AND deathv = 1 ) [ die] ] ask Sp94s [ if ( age < 3 AND ASQR94 < random-float 0.2 AND deathv = 1 ) [ die] ] ask Sp95s [ if ( age < 3 AND ASQR95 < random-float 0.3 AND deathv = 1 ) [ die] ] ask Sp96s [ if ( age < 3 AND ASQR96 < random-float 0.2 AND deathv = 1 ) [ die] ] ask Sp97s [ if ( age < 3 AND ASQR97 < random-float 0.3 AND deathv = 1 ) [ die] ] ask Sp98s [ if ( age < 3 AND ASQR98 < random-float 0.2 AND deathv = 1 ) [ die] ] ask Sp99s [ if ( age < 3 AND ASQR99 < random-float 0.3 AND deathv = 1 ) [ die] ] ask Sp100s [ if ( age < 3 AND ASQR100 < random-float 0.2 AND deathv = 1 ) [ die ] ] end ; THE UBI SUBROUTINE ADDS LONG DISTANCE DISPERSAL FROM OFF THE GRID FOR THE UBIQUITOUS DISPERSERS to ubi random-seed seed + 350 repeat 1 [ ask patch random 100 random 100 [ sprout-Sp1s 1 [ set size 1 set deathv 2 set age 0 ] ] ask patch random 100 random 100 [ sprout-Sp3s 1 [ set size 1 set deathv 2 set age 0 ] ] ask patch random 100 random 100 [ sprout-Sp5s 1 [ set size 1 set deathv 2 set age 0 ] ] ask patch random 100 random 100 [ sprout-Sp7s 1 [ set size 1 set deathv 2 set age 0 ] ] ask patch random 100 random 100 [ sprout-Sp9s 1 [ set size 1 set deathv 2 set age 0 ] ] ask patch random 100 random 100 [ sprout-Sp11s 1 [ set size 1 set deathv 2 set age 0 ] ] ask patch random 100 random 100 [ sprout-Sp13s 1 [ set size 1 set deathv 2 set age 0 ] ] ask patch random 100 random 100 [ sprout-Sp15s 1 [ set size 1 set deathv 2 set age 0 ] ] ask patch random 100 random 100 [ sprout-Sp17s 1 [ set size 1 set deathv 2 set age 0 ] ] ask patch random 100 random 100 [ sprout-Sp19s 1 [ set size 1 set deathv 2 set age 0 ] ] ask patch random 100 random 100 [ sprout-Sp21s 1 [ set size 1 set deathv 2 set age 0 ] ] ask patch random 100 random 100 [ sprout-Sp23s 1 [ set size 1 set deathv 2 set age 0 ] ] ask patch random 100 random 100 [ sprout-Sp25s 1 [ set size 1 set deathv 2 set age 0 ] ] ask patch random 100 random 100 [ sprout-Sp27s 1 [ set size 1 set deathv 2 set age 0 ] ] ask patch random 100 random 100 [ sprout-Sp29s 1 [ set size 1 set deathv 2 set age 0 ] ] ask patch random 100 random 100 [ sprout-Sp31s 1 [ set size 1 set deathv 2 set age 0 ] ] ask patch random 100 random 100 [ sprout-Sp33s 1 [ set size 1 set deathv 2 set age 0 ] ] ask patch random 100 random 100 [ sprout-Sp35s 1 [ set size 1 set deathv 2 set age 0 ] ] ask patch random 100 random 100 [ sprout-Sp37s 1 [ set size 1 set deathv 2 set age 0 ] ] ask patch random 100 random 100 [ sprout-Sp39s 1 [ set size 1 set deathv 2 set age 0 ] ] ask patch random 100 random 100 [ sprout-Sp41s 1 [ set size 1 set deathv 2 set age 0 ] ] ask patch random 100 random 100 [ sprout-Sp43s 1 [ set size 1 set deathv 2 set age 0 ] ] ask patch random 100 random 100 [ sprout-Sp45s 1 [ set size 1 set deathv 2 set age 0 ] ] ask patch random 100 random 100 [ sprout-Sp47s 1 [ set size 1 set deathv 2 set age 0 ] ] ask patch random 100 random 100 [ sprout-Sp49s 1 [ set size 1 set deathv 2 set age 0 ] ] ask patch random 100 random 100 [ sprout-Sp51s 1 [ set size 1 set deathv 2 set age 0 ] ] ask patch random 100 random 100 [ sprout-Sp53s 1 [ set size 1 set deathv 2 set age 0 ] ] ask patch random 100 random 100 [ sprout-Sp55s 1 [ set size 1 set deathv 2 set age 0 ] ] ask patch random 100 random 100 [ sprout-Sp57s 1 [ set size 1 set deathv 2 set age 0 ] ] ask patch random 100 random 100 [ sprout-Sp59s 1 [ set size 1 set deathv 2 set age 0 ] ] ask patch random 100 random 100 [ sprout-Sp61s 1 [ set size 1 set deathv 2 set age 0 ] ] ask patch random 100 random 100 [ sprout-Sp63s 1 [ set size 1 set deathv 2 set age 0 ] ] ask patch random 100 random 100 [ sprout-Sp65s 1 [ set size 1 set deathv 2 set age 0 ] ] ask patch random 100 random 100 [ sprout-Sp67s 1 [ set size 1 set deathv 2 set age 0 ] ] ask patch random 100 random 100 [ sprout-Sp69s 1 [ set size 1 set deathv 2 set age 0 ] ] ask patch random 100 random 100 [ sprout-Sp71s 1 [ set size 1 set deathv 2 set age 0 ] ] ask patch random 100 random 100 [ sprout-Sp73s 1 [ set size 1 set deathv 2 set age 0 ] ] ask patch random 100 random 100 [ sprout-Sp75s 1 [ set size 1 set deathv 2 set age 0 ] ] ask patch random 100 random 100 [ sprout-Sp77s 1 [ set size 1 set deathv 2 set age 0 ] ] ask patch random 100 random 100 [ sprout-Sp79s 1 [ set size 1 set deathv 2 set age 0 ] ] ask patch random 100 random 100 [ sprout-Sp81s 1 [ set size 1 set deathv 2 set age 0 ] ] ask patch random 100 random 100 [ sprout-Sp83s 1 [ set size 1 set deathv 2 set age 0 ] ] ask patch random 100 random 100 [ sprout-Sp85s 1 [ set size 1 set deathv 2 set age 0 ] ] ask patch random 100 random 100 [ sprout-Sp87s 1 [ set size 1 set deathv 2 set age 0 ] ] ask patch random 100 random 100 [ sprout-Sp89s 1 [ set size 1 set deathv 2 set age 0 ] ] ask patch random 100 random 100 [ sprout-Sp91s 1 [ set size 1 set deathv 2 set age 0 ] ] ask patch random 100 random 100 [ sprout-Sp93s 1 [ set size 1 set deathv 2 set age 0 ] ] ask patch random 100 random 100 [ sprout-Sp95s 1 [ set size 1 set deathv 2 set age 0 ] ] ask patch random 100 random 100 [ sprout-Sp97s 1 [ set size 1 set deathv 2 set age 0 ] ] ask patch random 100 random 100 [ sprout-Sp99s 1 [ set size 1 set deathv 2 set age 0 ] ] ;] ] death4 end ; THE DEATH4 SUBROUTINE KILLS INDIVIDUALS THAT HAVE DISPERSED IN FROM OFF THE GRID to death4 random-seed seed + 300 ask Sp1s [ if ( age < 3 AND ASQR1 < random-float 0.3 AND deathv = 2 ) [ die] ] ask Sp3s [ if ( age < 3 AND ASQR3 < random-float 0.3 AND deathv = 2 ) [ die] ] ask Sp5s [ if ( age < 3 AND ASQR5 < random-float 0.3 AND deathv = 2 ) [ die] ] ask Sp7s [ if ( age < 3 AND ASQR7 < random-float 0.3 AND deathv = 2 ) [ die] ] ask Sp9s [ if ( age < 3 AND ASQR9 < random-float 0.3 AND deathv = 2 ) [ die] ] ask Sp11s [ if ( age < 3 AND ASQR11 < random-float 0.3 AND deathv = 2 ) [ die] ] ask Sp13s [ if ( age < 3 AND ASQR13 < random-float 0.3 AND deathv = 2 ) [ die] ] ask Sp15s [ if ( age < 3 AND ASQR15 < random-float 0.3 AND deathv = 2 ) [ die] ] ask Sp17s [ if ( age < 3 AND ASQR17 < random-float 0.3 AND deathv = 2 ) [ die] ] ask Sp19s [ if ( age < 3 AND ASQR19 < random-float 0.3 AND deathv = 2 ) [ die] ] ask Sp21s [ if ( age < 3 AND ASQR21 < random-float 0.3 AND deathv = 2 ) [ die] ] ask Sp23s [ if ( age < 3 AND ASQR23 < random-float 0.3 AND deathv = 2 ) [ die] ] ask Sp25s [ if ( age < 3 AND ASQR25 < random-float 0.3 AND deathv = 2 ) [ die] ] ask Sp27s [ if ( age < 3 AND ASQR27 < random-float 0.3 AND deathv = 2 ) [ die] ] ask Sp29s [ if ( age < 3 AND ASQR29 < random-float 0.3 AND deathv = 2 ) [ die] ] ask Sp31s [ if ( age < 3 AND ASQR31 < random-float 0.3 AND deathv = 2 ) [ die] ] ask Sp33s [ if ( age < 3 AND ASQR33 < random-float 0.3 AND deathv = 2 ) [ die] ] ask Sp35s [ if ( age < 3 AND ASQR35 < random-float 0.3 AND deathv = 2 ) [ die] ] ask Sp37s [ if ( age < 3 AND ASQR37 < random-float 0.3 AND deathv = 2 ) [ die] ] ask Sp39s [ if ( age < 3 AND ASQR39 < random-float 0.3 AND deathv = 2 ) [ die] ] ask Sp41s [ if ( age < 3 AND ASQR41 < random-float 0.3 AND deathv = 2 ) [ die] ] ask Sp43s [ if ( age < 3 AND ASQR43 < random-float 0.3 AND deathv = 2 ) [ die] ] ask Sp45s [ if ( age < 3 AND ASQR45 < random-float 0.3 AND deathv = 2 ) [ die] ] ask Sp47s [ if ( age < 3 AND ASQR47 < random-float 0.3 AND deathv = 2 ) [ die] ] ask Sp49s [ if ( age < 3 AND ASQR49 < random-float 0.3 AND deathv = 2 ) [ die] ] ask Sp51s [ if ( age < 3 AND ASQR51 < random-float 0.3 AND deathv = 2 ) [ die] ] ask Sp53s [ if ( age < 3 AND ASQR53 < random-float 0.3 AND deathv = 2 ) [ die] ] ask Sp55s [ if ( age < 3 AND ASQR55 < random-float 0.3 AND deathv = 2 ) [ die] ] ask Sp57s [ if ( age < 3 AND ASQR57 < random-float 0.2 AND deathv = 2 ) [ die] ] ask Sp59s [ if ( age < 3 AND ASQR59 < random-float 0.2 AND deathv = 2 ) [ die] ] ask Sp61s [ if ( age < 3 AND ASQR61 < random-float 0.2 AND deathv = 2 ) [ die] ] ask Sp63s [ if ( age < 3 AND ASQR63 < random-float 0.2 AND deathv = 2 ) [ die] ] ask Sp65s [ if ( age < 3 AND ASQR65 < random-float 0.2 AND deathv = 2 ) [ die] ] ask Sp67s [ if ( age < 3 AND ASQR67 < random-float 0.2 AND deathv = 2 ) [ die] ] ask Sp69s [ if ( age < 3 AND ASQR69 < random-float 0.2 AND deathv = 2 ) [ die] ] ask Sp71s [ if ( age < 3 AND ASQR71 < random-float 0.2 AND deathv = 2 ) [ die] ] ask Sp73s [ if ( age < 3 AND ASQR73 < random-float 0.2 AND deathv = 2 ) [ die] ] ask Sp75s [ if ( age < 3 AND ASQR75 < random-float 0.2 AND deathv = 2 ) [ die] ] ask Sp77s [ if ( age < 3 AND ASQR77 < random-float 0.2 AND deathv = 2 ) [ die] ] ask Sp79s [ if ( age < 3 AND ASQR79 < random-float 0.2 AND deathv = 2 ) [ die] ] ask Sp81s [ if ( age < 3 AND ASQR81 < random-float 0.2 AND deathv = 2 ) [ die] ] ask Sp83s [ if ( age < 3 AND ASQR83 < random-float 0.2 AND deathv = 2 ) [ die] ] ask Sp85s [ if ( age < 3 AND ASQR85 < random-float 0.2 AND deathv = 2 ) [ die] ] ask Sp87s [ if ( age < 3 AND ASQR87 < random-float 0.2 AND deathv = 2 ) [ die] ] ask Sp89s [ if ( age < 3 AND ASQR89 < random-float 0.2 AND deathv = 2 ) [ die] ] ask Sp91s [ if ( age < 3 AND ASQR91 < random-float 0.2 AND deathv = 2 ) [ die] ] ask Sp93s [ if ( age < 3 AND ASQR93 < random-float 0.3 AND deathv = 2 ) [ die] ] ask Sp95s [ if ( age < 3 AND ASQR95 < random-float 0.3 AND deathv = 2 ) [ die] ] ask Sp97s [ if ( age < 3 AND ASQR97 < random-float 0.3 AND deathv = 2 ) [ die] ] ask Sp99s [ if ( age < 3 AND ASQR99 < random-float 0.3 AND deathv = 2 ) [ die] ] end ; THE RICH SUBROUTINE CALCULATES THE NUMBER OF SPECIES CONSERVED AT THE END OF THE SIMULATION, NOT INCLUDING SEEDLINGS to rich set gamma 0 if ( count Sp1s with [age > 2] > 1) [set gamma gamma + 1] if ( count Sp2s with [age > 2] > 1) [set gamma gamma + 1] if ( count Sp3s with [age > 2] > 1) [set gamma gamma + 1] if ( count Sp4s with [age > 2] > 1) [set gamma gamma + 1] if ( count Sp5s with [age > 2] > 1) [set gamma gamma + 1] if ( count Sp6s with [age > 2] > 1) [set gamma gamma + 1] if ( count Sp7s with [age > 2] > 1) [set gamma gamma + 1] if ( count Sp8s with [age > 2] > 1) [set gamma gamma + 1] if ( count Sp9s with [age > 2] > 1) [set gamma gamma + 1] if ( count Sp10s with [age > 2] > 1) [set gamma gamma + 1] if ( count Sp11s with [age > 2] > 1) [set gamma gamma + 1] if ( count Sp12s with [age > 2] > 1) [set gamma gamma + 1] if ( count Sp13s with [age > 2] > 1) [set gamma gamma + 1] if ( count Sp14s with [age > 2] > 1) [set gamma gamma + 1] if ( count Sp18s with [age > 2] > 1) [set gamma gamma + 1] if ( count Sp16s with [age > 2] > 1) [set gamma gamma + 1] if ( count Sp17s with [age > 2] > 1) [set gamma gamma + 1] if ( count Sp18s with [age > 2] > 1) [set gamma gamma + 1] if ( count Sp19s with [age > 2] > 1) [set gamma gamma + 1] if ( count Sp20s with [age > 2] > 1) [set gamma gamma + 1] if ( count Sp21s with [age > 2] > 1) [set gamma gamma + 1] if ( count Sp22s with [age > 2] > 1) [set gamma gamma + 1] if ( count Sp23s with [age > 2] > 1) [set gamma gamma + 1] if ( count Sp24s with [age > 2] > 1) [set gamma gamma + 1] if ( count Sp25s with [age > 2] > 1) [set gamma gamma + 1] if ( count Sp26s with [age > 2] > 1) [set gamma gamma + 1] if ( count Sp27s with [age > 2] > 1) [set gamma gamma + 1] if ( count Sp28s with [age > 2] > 1) [set gamma gamma + 1] if ( count Sp29s with [age > 2] > 1) [set gamma gamma + 1] if ( count Sp30s with [age > 2] > 1) [set gamma gamma + 1] if ( count Sp31s with [age > 2] > 1) [set gamma gamma + 1] if ( count Sp32s with [age > 2] > 1) [set gamma gamma + 1] if ( count Sp33s with [age > 2] > 1) [set gamma gamma + 1] if ( count Sp34s with [age > 2] > 1) [set gamma gamma + 1] if ( count Sp35s with [age > 2] > 1) [set gamma gamma + 1] if ( count Sp36s with [age > 2] > 1) [set gamma gamma + 1] if ( count Sp37s with [age > 2] > 1) [set gamma gamma + 1] if ( count Sp38s with [age > 2] > 1) [set gamma gamma + 1] if ( count Sp39s with [age > 2] > 1) [set gamma gamma + 1] if ( count Sp40s with [age > 2] > 1) [set gamma gamma + 1] if ( count Sp41s with [age > 2] > 1) [set gamma gamma + 1] if ( count Sp42s with [age > 2] > 1) [set gamma gamma + 1] if ( count Sp43s with [age > 2] > 1) [set gamma gamma + 1] if ( count Sp44s with [age > 2] > 1) [set gamma gamma + 1] if ( count Sp45s with [age > 2] > 1) [set gamma gamma + 1] if ( count Sp46s with [age > 2] > 1) [set gamma gamma + 1] if ( count Sp47s with [age > 2] > 1) [set gamma gamma + 1] if ( count Sp48s with [age > 2] > 1) [set gamma gamma + 1] if ( count Sp49s with [age > 2] > 1) [set gamma gamma + 1] if ( count Sp50s with [age > 2] > 1) [set gamma gamma + 1] if ( count Sp51s with [age > 2] > 1) [set gamma gamma + 1] if ( count Sp52s with [age > 2] > 1) [set gamma gamma + 1] if ( count Sp53s with [age > 2] > 1) [set gamma gamma + 1] if ( count Sp54s with [age > 2] > 1) [set gamma gamma + 1] if ( count Sp55s with [age > 2] > 1) [set gamma gamma + 1] if ( count Sp56s with [age > 2] > 1) [set gamma gamma + 1] if ( count Sp57s with [age > 2] > 1) [set gamma gamma + 1] if ( count Sp58s with [age > 2] > 1) [set gamma gamma + 1] if ( count Sp59s with [age > 2] > 1) [set gamma gamma + 1] if ( count Sp60s with [age > 2] > 1) [set gamma gamma + 1] if ( count Sp61s with [age > 2] > 1) [set gamma gamma + 1] if ( count Sp62s with [age > 2] > 1) [set gamma gamma + 1] if ( count Sp63s with [age > 2] > 1) [set gamma gamma + 1] if ( count Sp64s with [age > 2] > 1) [set gamma gamma + 1] if ( count Sp65s with [age > 2] > 1) [set gamma gamma + 1] if ( count Sp66s with [age > 2] > 1) [set gamma gamma + 1] if ( count Sp67s with [age > 2] > 1) [set gamma gamma + 1] if ( count Sp68s with [age > 2] > 1) [set gamma gamma + 1] if ( count Sp69s with [age > 2] > 1) [set gamma gamma + 1] if ( count Sp70s with [age > 2] > 1) [set gamma gamma + 1] if ( count Sp71s with [age > 2] > 1) [set gamma gamma + 1] if ( count Sp72s with [age > 2] > 1) [set gamma gamma + 1] if ( count Sp73s with [age > 2] > 1) [set gamma gamma + 1] if ( count Sp74s with [age > 2] > 1) [set gamma gamma + 1] if ( count Sp75s with [age > 2] > 1) [set gamma gamma + 1] if ( count Sp76s with [age > 2] > 1) [set gamma gamma + 1] if ( count Sp77s with [age > 2] > 1) [set gamma gamma + 1] if ( count Sp78s with [age > 2] > 1) [set gamma gamma + 1] if ( count Sp79s with [age > 2] > 1) [set gamma gamma + 1] if ( count Sp80s with [age > 2] > 1) [set gamma gamma + 1] if ( count Sp81s with [age > 2] > 1) [set gamma gamma + 1] if ( count Sp82s with [age > 2] > 1) [set gamma gamma + 1] if ( count Sp83s with [age > 2] > 1) [set gamma gamma + 1] if ( count Sp84s with [age > 2] > 1) [set gamma gamma + 1] if ( count Sp85s with [age > 2] > 1) [set gamma gamma + 1] if ( count Sp86s with [age > 2] > 1) [set gamma gamma + 1] if ( count Sp87s with [age > 2] > 1) [set gamma gamma + 1] if ( count Sp88s with [age > 2] > 1) [set gamma gamma + 1] if ( count Sp89s with [age > 2] > 1) [set gamma gamma + 1] if ( count Sp90s with [age > 2] > 1) [set gamma gamma + 1] if ( count Sp91s with [age > 2] > 1) [set gamma gamma + 1] if ( count Sp92s with [age > 2] > 1) [set gamma gamma + 1] if ( count Sp93s with [age > 2] > 1) [set gamma gamma + 1] if ( count Sp94s with [age > 2] > 1) [set gamma gamma + 1] if ( count Sp95s with [age > 2] > 1) [set gamma gamma + 1] if ( count Sp96s with [age > 2] > 1) [set gamma gamma + 1] if ( count Sp97s with [age > 2] > 1) [set gamma gamma + 1] if ( count Sp98s with [age > 2] > 1) [set gamma gamma + 1] if ( count Sp99s with [age > 2] > 1) [set gamma gamma + 1] if (count Sp100s with [age > 2] > 1) [set gamma gamma + 1] end ; THE OUTCOUNT SUBROUTINE PRINTS THE NUMBER OF INDIVIDUALS OF EACH SPECIES THAT ARE ; EXTANT ANYWHERE ON THE GRID to outcount1 print year print count Sp1s print count Sp2s print count Sp3s print count Sp4s print count Sp5s print count Sp6s print count Sp7s print count Sp8s print count Sp9s print count Sp10s print count Sp11s print count Sp12s print count Sp13s print count Sp14s print count Sp18s print count Sp16s print count Sp17s print count Sp18s print count Sp19s print count Sp20s print count Sp21s print count Sp22s print count Sp23s print count Sp24s print count Sp25s print count Sp26s print count Sp27s print count Sp28s print count Sp29s print count Sp30s print count Sp31s print count Sp32s print count Sp33s print count Sp34s print count Sp35s print count Sp36s print count Sp37s print count Sp38s print count Sp39s print count Sp40s print count Sp41s print count Sp42s print count Sp43s print count Sp44s print count Sp45s print count Sp46s print count Sp47s print count Sp48s print count Sp49s print count Sp50s print count Sp51s print count Sp52s print count Sp53s print count Sp54s print count Sp55s print count Sp56s print count Sp57s print count Sp58s print count Sp59s print count Sp60s print count Sp61s print count Sp62s print count Sp63s print count Sp64s print count Sp65s print count Sp66s print count Sp67s print count Sp68s print count Sp69s print count Sp70s print count Sp71s print count Sp72s print count Sp73s print count Sp74s print count Sp75s print count Sp76s print count Sp77s print count Sp78s print count Sp79s print count Sp80s print count Sp81s print count Sp82s print count Sp83s print count Sp84s print count Sp85s print count Sp86s print count Sp87s print count Sp88s print count Sp89s print count Sp90s print count Sp91s print count Sp92s print count Sp93s print count Sp94s print count Sp95s print count Sp96s print count Sp97s print count Sp98s print count Sp99s print count Sp100s end to outcount2 print year print count patches with [climate4 < 0.95] print count patches with [climate4 < 0.9] print count patches with [climate4 < 0.85] print count patches with [climate4 < 0.8] print count patches with [climate4 < 0.75] print count patches with [climate4 < 0.7] print count patches with [climate4 < 0.65] print count patches with [climate4 < 0.6] print count patches with [climate4 < 0.55] print count patches with [climate4 < 0.5] print count patches with [climate4 < 0.45] print count patches with [climate4 < 0.4] print count patches with [climate4 < 0.35] print count patches with [climate4 < 0.3] print count patches with [climate4 < 0.25] print count patches with [climate4 < 0.2] print count patches with [climate4 < 0.15] print count patches with [climate4 < 0.1] print count patches with [climate4 < 0.05] end to outcount3 print year ask patches [ set alpha 0 if (count Sp1s-here > 0) [ set alpha alpha + 1 ] if (count Sp2s-here > 0) [ set alpha alpha + 1 ] if (count Sp3s-here > 0) [ set alpha alpha + 1 ] if (count Sp4s-here > 0) [ set alpha alpha + 1 ] if (count Sp5s-here > 0) [ set alpha alpha + 1 ] if (count Sp6s-here > 0) [ set alpha alpha + 1 ] if (count Sp7s-here > 0) [ set alpha alpha + 1 ] if (count Sp8s-here > 0) [ set alpha alpha + 1 ] if (count Sp9s-here > 0) [ set alpha alpha + 1 ] if (count Sp10s-here > 0) [ set alpha alpha + 1 ] if (count Sp11s-here > 0) [ set alpha alpha + 1 ] if (count Sp12s-here > 0) [ set alpha alpha + 1 ] if (count Sp13s-here > 0) [ set alpha alpha + 1 ] if (count Sp14s-here > 0) [ set alpha alpha + 1 ] if (count Sp18s-here > 0) [ set alpha alpha + 1 ] if (count Sp16s-here > 0) [ set alpha alpha + 1 ] if (count Sp17s-here > 0) [ set alpha alpha + 1 ] if (count Sp18s-here > 0) [ set alpha alpha + 1 ] if (count Sp19s-here > 0) [ set alpha alpha + 1 ] if (count Sp20s-here > 0) [ set alpha alpha + 1 ] if (count Sp21s-here > 0) [ set alpha alpha + 1 ] if (count Sp22s-here > 0) [ set alpha alpha + 1 ] if (count Sp23s-here > 0) [ set alpha alpha + 1 ] if (count Sp24s-here > 0) [ set alpha alpha + 1 ] if (count Sp25s-here > 0) [ set alpha alpha + 1 ] if (count Sp26s-here > 0) [ set alpha alpha + 1 ] if (count Sp27s-here > 0) [ set alpha alpha + 1 ] if (count Sp28s-here > 0) [ set alpha alpha + 1 ] if (count Sp29s-here > 0) [ set alpha alpha + 1 ] if (count Sp30s-here > 0) [ set alpha alpha + 1 ] if (count Sp31s-here > 0) [ set alpha alpha + 1 ] if (count Sp32s-here > 0) [ set alpha alpha + 1 ] if (count Sp33s-here > 0) [ set alpha alpha + 1 ] if (count Sp34s-here > 0) [ set alpha alpha + 1 ] if (count Sp35s-here > 0) [ set alpha alpha + 1 ] if (count Sp36s-here > 0) [ set alpha alpha + 1 ] if (count Sp37s-here > 0) [ set alpha alpha + 1 ] if (count Sp38s-here > 0) [ set alpha alpha + 1 ] if (count Sp39s-here > 0) [ set alpha alpha + 1 ] if (count Sp40s-here > 0) [ set alpha alpha + 1 ] if (count Sp41s-here > 0) [ set alpha alpha + 1 ] if (count Sp42s-here > 0) [ set alpha alpha + 1 ] if (count Sp43s-here > 0) [ set alpha alpha + 1 ] if (count Sp44s-here > 0) [ set alpha alpha + 1 ] if (count Sp45s-here > 0) [ set alpha alpha + 1 ] if (count Sp46s-here > 0) [ set alpha alpha + 1 ] if (count Sp47s-here > 0) [ set alpha alpha + 1 ] if (count Sp48s-here > 0) [ set alpha alpha + 1 ] if (count Sp49s-here > 0) [ set alpha alpha + 1 ] if (count Sp50s-here > 0) [ set alpha alpha + 1 ] if (count Sp51s-here > 0) [ set alpha alpha + 1 ] if (count Sp52s-here > 0) [ set alpha alpha + 1 ] if (count Sp53s-here > 0) [ set alpha alpha + 1 ] if (count Sp54s-here > 0) [ set alpha alpha + 1 ] if (count Sp55s-here > 0) [ set alpha alpha + 1 ] if (count Sp56s-here > 0) [ set alpha alpha + 1 ] if (count Sp57s-here > 0) [ set alpha alpha + 1 ] if (count Sp58s-here > 0) [ set alpha alpha + 1 ] if (count Sp59s-here > 0) [ set alpha alpha + 1 ] if (count Sp60s-here > 0) [ set alpha alpha + 1 ] if (count Sp61s-here > 0) [ set alpha alpha + 1 ] if (count Sp62s-here > 0) [ set alpha alpha + 1 ] if (count Sp63s-here > 0) [ set alpha alpha + 1 ] if (count Sp64s-here > 0) [ set alpha alpha + 1 ] if (count Sp65s-here > 0) [ set alpha alpha + 1 ] if (count Sp66s-here > 0) [ set alpha alpha + 1 ] if (count Sp67s-here > 0) [ set alpha alpha + 1 ] if (count Sp68s-here > 0) [ set alpha alpha + 1 ] if (count Sp69s-here > 0) [ set alpha alpha + 1 ] if (count Sp70s-here > 0) [ set alpha alpha + 1 ] if (count Sp71s-here > 0) [ set alpha alpha + 1 ] if (count Sp72s-here > 0) [ set alpha alpha + 1 ] if (count Sp73s-here > 0) [ set alpha alpha + 1 ] if (count Sp74s-here > 0) [ set alpha alpha + 1 ] if (count Sp75s-here > 0) [ set alpha alpha + 1 ] if (count Sp76s-here > 0) [ set alpha alpha + 1 ] if (count Sp77s-here > 0) [ set alpha alpha + 1 ] if (count Sp78s-here > 0) [ set alpha alpha + 1 ] if (count Sp79s-here > 0) [ set alpha alpha + 1 ] if (count Sp80s-here > 0) [ set alpha alpha + 1 ] if (count Sp81s-here > 0) [ set alpha alpha + 1 ] if (count Sp82s-here > 0) [ set alpha alpha + 1 ] if (count Sp83s-here > 0) [ set alpha alpha + 1 ] if (count Sp84s-here > 0) [ set alpha alpha + 1 ] if (count Sp85s-here > 0) [ set alpha alpha + 1 ] if (count Sp86s-here > 0) [ set alpha alpha + 1 ] if (count Sp87s-here > 0) [ set alpha alpha + 1 ] if (count Sp88s-here > 0) [ set alpha alpha + 1 ] if (count Sp89s-here > 0) [ set alpha alpha + 1 ] if (count Sp90s-here > 0) [ set alpha alpha + 1 ] if (count Sp91s-here > 0) [ set alpha alpha + 1 ] if (count Sp92s-here > 0) [ set alpha alpha + 1 ] if (count Sp93s-here > 0) [ set alpha alpha + 1 ] if (count Sp94s-here > 0) [ set alpha alpha + 1 ] if (count Sp95s-here > 0) [ set alpha alpha + 1 ] if (count Sp96s-here > 0) [ set alpha alpha + 1 ] if (count Sp97s-here > 0) [ set alpha alpha + 1 ] if (count Sp98s-here > 0) [ set alpha alpha + 1 ] if (count Sp99s-here > 0) [ set alpha alpha + 1 ] if (count Sp100s-here > 0) [ set alpha alpha + 1 ] print pxcor print pycor print alpha ] end
There is only one version of this model, created over 1 year ago by George Malanson.
Attached files
| File | Type | Description | Last updated | |
|---|---|---|---|---|
| JBI_buffer_effectiveness.png | preview | Preview for 'JBI_buffer_effectiveness' | over 1 year ago, by George Malanson | Download |
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