{"title":"What do functional diversity, redundancy, rarity, and originality actually measure? A theoretical guide for ecologists and conservationists","authors":"Carlo Ricotta , Sandrine Pavoine","doi":"10.1016/j.ecocom.2025.101116","DOIUrl":null,"url":null,"abstract":"<div><div>Functional diversity, redundancy, rarity, and originality (or distinctiveness) are fundamental concepts in ecology and conservation biology. Despite their frequent use, the precise meaning and relationships between these measures are often unclear. This paper aims to provide a comprehensive theoretical framework to elucidate what each of these measures captures and how they interrelate. By integrating traditional community-level diversity metrics with species-level specificity measures derived from fuzzy set theory, we bridge the gap between these concepts. Our framework reveals that while all four measures address distinct aspects of community-level and species-level functional resemblance, they can all be traced back to a common conceptual and formal background. This guide is intended to help ecologists and conservationists understand the meaning of these measures and apply them more effectively in their research and conservation strategies.</div></div>","PeriodicalId":50559,"journal":{"name":"Ecological Complexity","volume":"61 ","pages":"Article 101116"},"PeriodicalIF":3.1000,"publicationDate":"2025-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Ecological Complexity","FirstCategoryId":"93","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S1476945X25000017","RegionNum":3,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"ECOLOGY","Score":null,"Total":0}
引用次数: 0
Abstract
Functional diversity, redundancy, rarity, and originality (or distinctiveness) are fundamental concepts in ecology and conservation biology. Despite their frequent use, the precise meaning and relationships between these measures are often unclear. This paper aims to provide a comprehensive theoretical framework to elucidate what each of these measures captures and how they interrelate. By integrating traditional community-level diversity metrics with species-level specificity measures derived from fuzzy set theory, we bridge the gap between these concepts. Our framework reveals that while all four measures address distinct aspects of community-level and species-level functional resemblance, they can all be traced back to a common conceptual and formal background. This guide is intended to help ecologists and conservationists understand the meaning of these measures and apply them more effectively in their research and conservation strategies.
期刊介绍:
Ecological Complexity is an international journal devoted to the publication of high quality, peer-reviewed articles on all aspects of biocomplexity in the environment, theoretical ecology, and special issues on topics of current interest. The scope of the journal is wide and interdisciplinary with an integrated and quantitative approach. The journal particularly encourages submission of papers that integrate natural and social processes at appropriately broad spatio-temporal scales.
Ecological Complexity will publish research into the following areas:
• All aspects of biocomplexity in the environment and theoretical ecology
• Ecosystems and biospheres as complex adaptive systems
• Self-organization of spatially extended ecosystems
• Emergent properties and structures of complex ecosystems
• Ecological pattern formation in space and time
• The role of biophysical constraints and evolutionary attractors on species assemblages
• Ecological scaling (scale invariance, scale covariance and across scale dynamics), allometry, and hierarchy theory
• Ecological topology and networks
• Studies towards an ecology of complex systems
• Complex systems approaches for the study of dynamic human-environment interactions
• Using knowledge of nonlinear phenomena to better guide policy development for adaptation strategies and mitigation to environmental change
• New tools and methods for studying ecological complexity