Supplement 2. MATLAB function files to perform MCMC analysis and the analysis of covariance.

File List Road_map_to_programs.pdf (MD5: 6cabea12cc599775aadafa59fa0c87d2) readdata.m (MD5: 3bdfbc7154cb9aac0aa62d280824a911) nantest.m (MD5: 1053c9d8b0bb9605d7e5dd848d7c8555) matrixmcmcgr.m (MD5: 2ef6a1d52b626d669abcad0630dc2fdb) polyover.m (MD5: f00007a67b901771ff1ec5853a73861b) conpoly.m (MD5: 634b9340a0f7870e69b5f0a65967ae09) overlap.m (MD5: bc4038bbd510126a527ccfd4843087a3) permissible.m (MD5: 33ee427066e5ae51c3975d24a04362f6) actual_count.m (MD5: 7061c1d5e10b7c540c4c0fb0bc839a8a) actual_count_numshar.m (MD5: e9a93094a093c39e9a23bca65518fed0) pvals.m (MD5: 0dc6f6c67cbdfc69328ffb93f2ccfa97) pvals_numshar.m (MD5: 2aa826aa93072c4171ed06015331af01) polyover2.m (MD5: 406c9c9bb45c08d7b1f51fda35fe0a0f) fixpartial.m (MD5: a5ac36ba552b19151576c2b022b10d9b) simulated_count.m (MD5: f804cd8ab2638d8669de5a0f14006bd9) simulated_count_numshar.m (MD5: b131ba01d7ef613644e6082d144ad57d) ancova_prog.m (MD5: d3b1b7232d2f02a7bada58ade3d78911) Description PDF file Road_map_to_programs.pdf provides an overview of how the programs work together. MATLAB script file readdata.m reads in the data on species incidences, island group membership, and island coordinates. MATLAB script file nantest.m is called by readdata.m to convert not-a-number and uncertain status entries in the species occurrence matrix into absences. MATLAB script file matrixmcmcgr.m is the main program function for the MCMC analysis. MATLAB script file polyover.m uses the observed data to calculate overlap between each pair, and also creates index variables to code each pair as congeneric, within-guild, sharing island groups or not. MATLAB script file conpoly.m is called by polyover.m repeatedly to generate the coordinates on the convex hull for each species. MATLAB script file overlap.m uses the convexhulls to calculate the overlaps between pairs. MATLAB script file permissible.m creates a binary permissibility matrix. MATLAB script file actual_count.m generates the actual number of true complete checkerboards. MATLAB script file actual_count_numshar.m generates the actual number of true partial checkerbaords. MATLAB script file pvals.m generates the expected values, sd’s, and p values associated with tests based on defining a true complete checkerboard as observed overlap > expected overlap. MATLAB script file pvals_numshar.m generates the expected values, sd’s, and p values associated with tests based on defining a true partial checkerboard as observed overlap > expected overlap. MATLAB script file polyover2.m calculates the pair-wise overlap for each pair in a simulated matrix. MATLAB script file fixpartial.m determines which pairs are true partial checkerboards (TPC) at a variety of α levels. MATLAB script file simulated_count.m is used to determine in each simulated matrix which pairs are true complete checkerboards. MATLAB script file simulated_count_numshar.m is used to determine in each simulated matrix which pairs are true partial checkerboards. MATLAB script file ancova_prog.m performs the analysis of covariance using the observed and expected values generated by the simulation.### 文件列表 1. Road_map_to_programs.pdf（MD5：6cabea12cc599775aadafa59fa0c87d2） 2. readdata.m（MD5：3bdfbc7154cb9aac0aa62d280824a911） 3. nantest.m（MD5：1053c9d8b0bb9605d7e5dd848d7c8555） 4. matrixmcmcgr.m（MD5：2ef6a1d52b626d669abcad0630dc2fdb） 5. polyover.m（MD5：f00007a67b901771ff1ec5853a73861b） 6. conpoly.m（MD5：634b9340a0f7870e69b5f0a65967ae09） 7. overlap.m（MD5：bc4038bbd510126a527ccfd4843087a3） 8. permissible.m（MD5：33ee427066e5ae51c3975d24a04362f6） 9. actual_count.m（MD5：7061c1d5e10b7c540c4c0fb0bc839a8a） 10. actual_count_numshar.m（MD5：e9a93094a093c39e9a23bca65518fed0） 11. pvals.m（MD5：0dc6f6c67cbdfc69328ffb93f2ccfa97） 12. pvals_numshar.m（MD5：2aa826aa93072c417ed06015331af01） 13. polyover2.m（MD5：406c9c9bb45c08d7b1f51fda35fe0a0f） 14. fixpartial.m（MD5：a5ac36ba552b19151576c2b022b10d9b） 15. simulated_count.m（MD5：f804cd8ab2638d8669de5a0f14006bd9） 16. simulated_count_numshar.m（MD5：b131ba01d7ef613644e6082d144ad57d） 17. ancova_prog.m（MD5：d3b1b7232d2f02a7bada58ade3d78911） ### 数据集说明 本数据集的说明文档为Road_map_to_programs.pdf，该PDF文件概述了各程序的协同运行逻辑。 - readdata.m：MATLAB脚本，用于读取物种种群出现数据、岛屿群归属信息及岛屿坐标数据。 - nantest.m：MATLAB脚本，由readdata.m调用，用于将物种种群出现矩阵中的非数值（not-a-number）及不确定状态条目转换为未出现状态。 - matrixmcmcgr.m：MATLAB脚本，为马尔可夫链蒙特卡洛（Markov Chain Monte Carlo, MCMC）分析的主程序函数。 - polyover.m：MATLAB脚本，基于观测数据计算每对物种间的生态位重叠程度，并创建索引变量以将每对物种归类为同属、同功能群、共享岛屿群或非共享岛屿群。 - conpoly.m：MATLAB脚本，由polyover.m反复调用，用于生成每个物种的凸包坐标。 - overlap.m：MATLAB脚本，利用凸包计算每对物种间的重叠程度。 - permissible.m：MATLAB脚本，用于生成二进制可允许性矩阵。 - actual_count.m：MATLAB脚本，用于计算真实完整共存棋盘格局的实际数量。 - actual_count_numshar.m：MATLAB脚本，用于计算真实部分共存棋盘格局的实际数量。 - pvals.m：MATLAB脚本，用于生成基于“观测重叠度大于预期重叠度即定义为真实完整共存棋盘格局”的检验所对应的期望值、标准差及p值。 - pvals_numshar.m：MATLAB脚本，用于生成基于“观测重叠度大于预期重叠度即定义为真实部分共存棋盘格局”的检验所对应的期望值、标准差及p值。 - polyover2.m：MATLAB脚本，用于计算模拟种群矩阵中每对物种的成对重叠度。 - fixpartial.m：MATLAB脚本，用于确定在多个α显著性水平下，哪些物种对属于真实部分共存棋盘格局（TPC）。 - simulated_count.m：MATLAB脚本，用于确定每个模拟种群矩阵中哪些物种对属于真实完整共存棋盘格局。 - simulated_count_numshar.m：MATLAB脚本，用于确定每个模拟种群矩阵中哪些物种对属于真实部分共存棋盘格局。 - ancova_prog.m：MATLAB脚本，用于基于模拟生成的观测值与期望值进行协方差分析。