{"title":"利用相互作用特征来衡量食物网中物种的独特性","authors":"Wei-chung Liu , Ferenc Jordán","doi":"10.1016/j.ecolmodel.2025.111277","DOIUrl":null,"url":null,"abstract":"<div><div>Species are embedded in an intricate network of trophic interactions, it is therefore natural to examine species importance from a network perspective. In addition to measuring species importance by considering the centrality of their network positions in a food web (implying to be well connected to interaction partners), recent years have seen the emergence of species uniqueness (implying to be functionally harder to replace) as another facet of species importance. Existing network or food web-based uniqueness measurements are based on how species affect others and how their trophic fields may overlap. In this short communication paper, we demonstrate that it is also important to consider information on how species can be affected by others, and how this can be incorporated into species uniqueness measurement. We demonstrate our approach by analyzing in detail the Great Barrier Reef food web, and show how the inclusion of new information on species interaction pattern can change the uniqueness ranking of species. We further analyze 92 aquatic food webs to test the generality of our findings. For very few food webs, the correlation between species uniqueness rankings derived from the old and the new approaches is almost perfect. For the remaining food webs such a correlation varies, with many showing a medium level of correlation. Thus, including new information on species interaction pattern can offer new information on network or food web-based species uniqueness measurement.</div></div>","PeriodicalId":51043,"journal":{"name":"Ecological Modelling","volume":"509 ","pages":"Article 111277"},"PeriodicalIF":3.2000,"publicationDate":"2025-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Using interaction profile to measure species uniqueness in food webs\",\"authors\":\"Wei-chung Liu , Ferenc Jordán\",\"doi\":\"10.1016/j.ecolmodel.2025.111277\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><div>Species are embedded in an intricate network of trophic interactions, it is therefore natural to examine species importance from a network perspective. In addition to measuring species importance by considering the centrality of their network positions in a food web (implying to be well connected to interaction partners), recent years have seen the emergence of species uniqueness (implying to be functionally harder to replace) as another facet of species importance. Existing network or food web-based uniqueness measurements are based on how species affect others and how their trophic fields may overlap. In this short communication paper, we demonstrate that it is also important to consider information on how species can be affected by others, and how this can be incorporated into species uniqueness measurement. We demonstrate our approach by analyzing in detail the Great Barrier Reef food web, and show how the inclusion of new information on species interaction pattern can change the uniqueness ranking of species. We further analyze 92 aquatic food webs to test the generality of our findings. For very few food webs, the correlation between species uniqueness rankings derived from the old and the new approaches is almost perfect. For the remaining food webs such a correlation varies, with many showing a medium level of correlation. Thus, including new information on species interaction pattern can offer new information on network or food web-based species uniqueness measurement.</div></div>\",\"PeriodicalId\":51043,\"journal\":{\"name\":\"Ecological Modelling\",\"volume\":\"509 \",\"pages\":\"Article 111277\"},\"PeriodicalIF\":3.2000,\"publicationDate\":\"2025-08-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Ecological Modelling\",\"FirstCategoryId\":\"93\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S0304380025002637\",\"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}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Ecological Modelling","FirstCategoryId":"93","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0304380025002637","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}
Using interaction profile to measure species uniqueness in food webs
Species are embedded in an intricate network of trophic interactions, it is therefore natural to examine species importance from a network perspective. In addition to measuring species importance by considering the centrality of their network positions in a food web (implying to be well connected to interaction partners), recent years have seen the emergence of species uniqueness (implying to be functionally harder to replace) as another facet of species importance. Existing network or food web-based uniqueness measurements are based on how species affect others and how their trophic fields may overlap. In this short communication paper, we demonstrate that it is also important to consider information on how species can be affected by others, and how this can be incorporated into species uniqueness measurement. We demonstrate our approach by analyzing in detail the Great Barrier Reef food web, and show how the inclusion of new information on species interaction pattern can change the uniqueness ranking of species. We further analyze 92 aquatic food webs to test the generality of our findings. For very few food webs, the correlation between species uniqueness rankings derived from the old and the new approaches is almost perfect. For the remaining food webs such a correlation varies, with many showing a medium level of correlation. Thus, including new information on species interaction pattern can offer new information on network or food web-based species uniqueness measurement.
期刊介绍:
The journal is concerned with the use of mathematical models and systems analysis for the description of ecological processes and for the sustainable management of resources. Human activity and well-being are dependent on and integrated with the functioning of ecosystems and the services they provide. We aim to understand these basic ecosystem functions using mathematical and conceptual modelling, systems analysis, thermodynamics, computer simulations, and ecological theory. This leads to a preference for process-based models embedded in theory with explicit causative agents as opposed to strictly statistical or correlative descriptions. These modelling methods can be applied to a wide spectrum of issues ranging from basic ecology to human ecology to socio-ecological systems. The journal welcomes research articles, short communications, review articles, letters to the editor, book reviews, and other communications. The journal also supports the activities of the [International Society of Ecological Modelling (ISEM)](http://www.isemna.org/).