{"title":"StoX:种子传播效果的随机多阶段招募模型","authors":"Julio Martín-Herrero , María Calviño-Cancela","doi":"10.1016/j.simpa.2024.100673","DOIUrl":null,"url":null,"abstract":"<div><p>Seed dispersal effectiveness measures the number of new plants effectively produced by the services of seed disperser agents. This depends on a complex process involving multiple stages and actors, and has profound implications for conservation. StoX is a distribution agnostic multistage stochastic model that differentiates among dispersers in their contribution to seed rain and recruitment. It can be parameterized with quantity and quality components of dispersal measured in the field. It preserves the inherent stochastic nature of the recruitment process and can be validated by statistical comparison between its predictions and recruitment patterns in the field. StoX has already been used in several successful studies, at both population and community levels.</p></div>","PeriodicalId":29771,"journal":{"name":"Software Impacts","volume":"21 ","pages":"Article 100673"},"PeriodicalIF":1.3000,"publicationDate":"2024-06-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2665963824000617/pdfft?md5=9fd36c2e294a0983ef1b6080e174f371&pid=1-s2.0-S2665963824000617-main.pdf","citationCount":"0","resultStr":"{\"title\":\"StoX: Stochastic multistage recruitment model for seed dispersal effectiveness\",\"authors\":\"Julio Martín-Herrero , María Calviño-Cancela\",\"doi\":\"10.1016/j.simpa.2024.100673\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><p>Seed dispersal effectiveness measures the number of new plants effectively produced by the services of seed disperser agents. This depends on a complex process involving multiple stages and actors, and has profound implications for conservation. StoX is a distribution agnostic multistage stochastic model that differentiates among dispersers in their contribution to seed rain and recruitment. It can be parameterized with quantity and quality components of dispersal measured in the field. It preserves the inherent stochastic nature of the recruitment process and can be validated by statistical comparison between its predictions and recruitment patterns in the field. StoX has already been used in several successful studies, at both population and community levels.</p></div>\",\"PeriodicalId\":29771,\"journal\":{\"name\":\"Software Impacts\",\"volume\":\"21 \",\"pages\":\"Article 100673\"},\"PeriodicalIF\":1.3000,\"publicationDate\":\"2024-06-14\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.sciencedirect.com/science/article/pii/S2665963824000617/pdfft?md5=9fd36c2e294a0983ef1b6080e174f371&pid=1-s2.0-S2665963824000617-main.pdf\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Software Impacts\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S2665963824000617\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"COMPUTER SCIENCE, SOFTWARE ENGINEERING\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Software Impacts","FirstCategoryId":"1085","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S2665963824000617","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"COMPUTER SCIENCE, SOFTWARE ENGINEERING","Score":null,"Total":0}
StoX: Stochastic multistage recruitment model for seed dispersal effectiveness
Seed dispersal effectiveness measures the number of new plants effectively produced by the services of seed disperser agents. This depends on a complex process involving multiple stages and actors, and has profound implications for conservation. StoX is a distribution agnostic multistage stochastic model that differentiates among dispersers in their contribution to seed rain and recruitment. It can be parameterized with quantity and quality components of dispersal measured in the field. It preserves the inherent stochastic nature of the recruitment process and can be validated by statistical comparison between its predictions and recruitment patterns in the field. StoX has already been used in several successful studies, at both population and community levels.