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This exercise addresses classroom barriers caused by approach complexity and result interpretation by using readily available software and a hands-on workflow. Students can implement a low-cost activity as a standalone exercise or as preparation for larger simulations in follow-up labs, supported by curated data sets and simulation-based comparisons of observed checkerboard patterns against randomized communities.",{"@graph":69,"@context":121},[70,84,104],{"@type":71,"itemListElement":72},"BreadcrumbList",[73,77,79,82],{"item":74,"name":75,"@type":76,"position":8},"https://docshare.wps.com","Home","ListItem",{"item":78,"name":9,"@type":76,"position":14},"https://docshare.wps.com/document/",{"item":80,"name":40,"@type":76,"position":81},"https://docshare.wps.com/document/research-report/",3,{"item":83,"name":65,"@type":76,"position":19},"https://docshare.wps.com/document/null-models-for-everyone-a-two-step-approach-to-teaching-null-model-analysis-of-biological-community-structure/594663/",{"url":83,"name":65,"@type":85,"image":86,"author":91,"headline":65,"publisher":94,"fileFormat":97,"inLanguage":63,"description":67,"dateModified":98,"datePublished":98,"encodingFormat":97,"isAccessibleForFree":99,"interactionStatistic":100},"DigitalDocument",{"url":87,"@type":88,"width":89,"height":90},"https://docshare.wps.com/thumbnails/null-models-for-everyone-a-two-step-approach-to-teaching-null-model-analysis-of-biological-community-structure/594663.png","ImageObject",300,407,{"name":92,"@type":93},"Ben ","Person",{"url":74,"name":95,"@type":96},"DocShare","Organization","application/pdf","2026-10-15",true,{"@type":101,"interactionType":102,"userInteractionCount":4},"InteractionCounter",{"@type":103},"ViewAction",{"@type":105,"mainEntity":106},"FAQPage",[107,113,117],{"name":108,"@type":109,"acceptedAnswer":110},"What problem does this exercise aim to solve in teaching null model analysis?","Question",{"text":111,"@type":112},"It addresses the gap between the widespread use of null model analysis in the primary literature and the limited coverage in general ecology textbooks, focusing on making the technique accessible and interpretable for students.","Answer",{"name":114,"@type":109,"acceptedAnswer":115},"What are the core steps of running a null model analysis described here?",{"text":116,"@type":112},"The workflow calculates an index from an observed species-by-site presence-absence matrix, generates randomized communities under constraints, measures the index on each randomized community, repeats to build a histogram of null outcomes, and tests whether the observed index differs significantly from random assemblies.",{"name":118,"@type":109,"acceptedAnswer":119},"How do the exercises compare real community patterns to randomized expectations?",{"text":120,"@type":112},"They compare the number of checkerboard patterns observed in real community data to the frequency distribution of checkerboard patterns produced by randomized communities using simulations.","https://schema.org",{"og:url":83,"og:type":123,"og:title":65,"og:site_name":95,"og:description":67},"article",{"robots":125,"canonical":83},"index,follow",{"doc_id":127,"site_id":62},594663,1792079590,{"code":4,"msg":5,"data":130},{"doc_id":127,"user_id":131,"nickname":92,"user_avatar":132,"doc_module":4,"category_id":39,"category_name":40,"doc_title":65,"doc_description":67,"doc_content":133,"file_id":134,"file_url":135,"file_type":136,"file_size":137,"view_count":4,"is_deleted":4,"is_public":8,"is_downloadable":8,"audit_status":8,"page_count":52,"language":138,"language_code":63,"site_id":62,"html_lang":63,"table_of_contents":139,"faqs":140,"seo_title":141,"seo_description":67,"update_tm":128,"read_time":142},2336478951081,"https://ap-avatar.wpscdn.com/davatar_276721f389ce27ea32af1340a28f341c","Null Models for Everyone: A Two-Step Approach to Teaching Null Model Analysis of Biological Community Structure.  \nDeclan J. McCabe* and Evelyn J. Knight  \nSaint Michael’s College, Colchester, VT 05439  \n*Corresponding Author: [dmccabe@smcvt.edu](dmccabe@smcvt.edu)  \nAbstract: Since being introduced by Connor and Simberloffin response to Diamond’s assembly rules, null model analysis has been a controversial tool in community ecology. Despite being commonly used in the primary literature, null model analysis has not featured prominently in general textbooks. Complexity of approaches along with difficulty in interpreting results may reduce classroom application of this technique. Yet, readily available software makes this set of tools accessible to everyone from practitioners to educators. This exercise describes a hands-on approach that can be cheaply implemented with students as a stand-alone exercise or as a prelude to use of full-blown simulations in follow up lab sessions. Along with a detailed hands-on approach, we have provided a brief introduction to a computer-based approach. This paper includes a link to 294 data sets extracted from Patterson’s Nestedness software and reformatted for use in EcoSim. These exercises demonstrate how to compare the observed number of checkerboard patterns in real community data to a frequency distribution of checkerboard patterns in randomized communities. The hands-on simulation uses fake data as a starting point and dozens of randomizations to produce a histogram. Computer-based simulations generate thousands of simulations to rapidly analyze real data sets. The results provide a springboard for discussion of the underpinnings of inferential science as applied to ecological communities.  \nKeywords: Null model analysis; hands-on model; simulation; data mining; community ecology  \nINTRODUCTION  \nDiamond’s (1975) assembly rules were based upon the assumption that ecologists could recognize the fingerprints of competitive exclusion left on the distributions of species in natural communities. By examining the distributions of species pairs on archipelagosit is possible to identify species that never coexist on a single island. Diamond referred to such exclusive patterns as checkerboard distributions and contended that they were evidence of competitive exclusion. Connor and Simberloff (1983) countered that exclusive patterns were as likely to result from many other mechanisms including random chance. Null model analysis provides a way to statistically compare cooccurrence patterns of observed species distributions with those of randomly placed species.  \nTo run a null model analysis, investigators use the following simple steps (Gotelli and Entsminger, 2004):  \n1) . First we calculate an index that presumably tells us something about the structure of an observed set of natural communities summarized in a species by site presence-absence matrix (Table 1) . For the purposes of this exercise we will use the number of checkerboard distributions based on Diamond’s (1975) contention that checkerboard distributions are consistent with competitive exclusion.  \n2) . Subject to some constraints, we generatea set of randomized communities assembled absent the community structuring mechanism (competition in our example) .  \n3). We measure the index (number of checkerboards) from this randomized community.  \nTable 1. Initial placement of the beads in the trays. Any set of 7 unique colors will work to represent the species. Letters A through P represent the islands or sites where these species are found. If available ice cube trays have  \njust 14 wells, columns O and P can be omitted without drastically affecting the results.  \nSpecies A B C D E F G H I J K L M N O P  \n\n| Light Blue | 0 | 0 | 1 | 0 | 0 | 0 | 1 | 1 | 1 | 0 | 0 | 1 | 0 | 1 | 0 | 1 |\n| --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- |\n\n\n|  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |\n| -","cbCaiaLwG6GQRgW6","https://ap.wps.com/l/cbCaiaLwG6GQRgW6","pdf",363491,"English","# Introduction\n## Null model analysis overview\n## Steps for running a null model analysis\n# Rationale\n## Why null models are used yet under-taught\n## Two entry-level exercises","[{\"question\":\"What problem does this exercise aim to solve in teaching null model analysis?\",\"answer\":\"It addresses the gap between the widespread use of null model analysis in the primary literature and the limited coverage in general ecology textbooks, focusing on making the technique accessible and interpretable for students.\"},{\"question\":\"What are the core steps of running a null model analysis described here?\",\"answer\":\"The workflow calculates an index from an observed species-by-site presence-absence matrix, generates randomized communities under constraints, measures the index on each randomized community, repeats to build a histogram of null outcomes, and tests whether the observed index differs significantly from random assemblies.\"},{\"question\":\"How do the exercises compare real community patterns to randomized expectations?\",\"answer\":\"They compare the number of checkerboard patterns observed in real community data to the frequency distribution of checkerboard patterns produced by randomized communities using simulations.\"}]","Null Models for Everyone: A Two-Step Approach to Teaching Null Model Analysis of Biological Community Structure | PDF",25]