{"title":"评估适应性设计捕捉硬珊瑚覆盖趋势的能力","authors":"AWLP Thilan, P Menéndez, JM McGree","doi":"10.1002/env.2802","DOIUrl":null,"url":null,"abstract":"<p>Coral reefs have become one of the most vulnerable ecosystems worldwide due to rising environmental and anthropogenic pressures. Methods from experimental design can be used to furnish our ability to monitor such ecosystems efficiently. Recently, adaptive design approaches have been proposed for monitoring coral reefs; however, questions have surfaced around the ability of such approaches to capture trends over time. The aim of this study was to develop an approach to assess trends in hard coral cover and evaluate the effectiveness of adaptive designs for estimating such trends in coral reef communities within a region of the Great Barrier Reef. Our approach was couched within a Bayesian design and inference framework such that uncertainty was captured rigorously and so that information from accumulating data can be incorporated straightforwardly to inform future data collection. The designs found under this approach were compared to historical non-adaptive designs which surveyed all locations over time. Through this comparison, we show that adaptive designs can maintain trends over time with little to no loss in information, even when sampling effort is substantially reduced. Accordingly, this research serves to further promote adaptive design methods for efficiently and effectively sampling in ecological monitoring.</p>","PeriodicalId":50512,"journal":{"name":"Environmetrics","volume":"34 6","pages":""},"PeriodicalIF":1.5000,"publicationDate":"2023-05-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/env.2802","citationCount":"0","resultStr":"{\"title\":\"Assessing the ability of adaptive designs to capture trends in hard coral cover\",\"authors\":\"AWLP Thilan, P Menéndez, JM McGree\",\"doi\":\"10.1002/env.2802\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p>Coral reefs have become one of the most vulnerable ecosystems worldwide due to rising environmental and anthropogenic pressures. Methods from experimental design can be used to furnish our ability to monitor such ecosystems efficiently. Recently, adaptive design approaches have been proposed for monitoring coral reefs; however, questions have surfaced around the ability of such approaches to capture trends over time. The aim of this study was to develop an approach to assess trends in hard coral cover and evaluate the effectiveness of adaptive designs for estimating such trends in coral reef communities within a region of the Great Barrier Reef. Our approach was couched within a Bayesian design and inference framework such that uncertainty was captured rigorously and so that information from accumulating data can be incorporated straightforwardly to inform future data collection. The designs found under this approach were compared to historical non-adaptive designs which surveyed all locations over time. Through this comparison, we show that adaptive designs can maintain trends over time with little to no loss in information, even when sampling effort is substantially reduced. Accordingly, this research serves to further promote adaptive design methods for efficiently and effectively sampling in ecological monitoring.</p>\",\"PeriodicalId\":50512,\"journal\":{\"name\":\"Environmetrics\",\"volume\":\"34 6\",\"pages\":\"\"},\"PeriodicalIF\":1.5000,\"publicationDate\":\"2023-05-08\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://onlinelibrary.wiley.com/doi/epdf/10.1002/env.2802\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Environmetrics\",\"FirstCategoryId\":\"93\",\"ListUrlMain\":\"https://onlinelibrary.wiley.com/doi/10.1002/env.2802\",\"RegionNum\":3,\"RegionCategory\":\"环境科学与生态学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q4\",\"JCRName\":\"ENVIRONMENTAL SCIENCES\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Environmetrics","FirstCategoryId":"93","ListUrlMain":"https://onlinelibrary.wiley.com/doi/10.1002/env.2802","RegionNum":3,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"ENVIRONMENTAL SCIENCES","Score":null,"Total":0}
Assessing the ability of adaptive designs to capture trends in hard coral cover
Coral reefs have become one of the most vulnerable ecosystems worldwide due to rising environmental and anthropogenic pressures. Methods from experimental design can be used to furnish our ability to monitor such ecosystems efficiently. Recently, adaptive design approaches have been proposed for monitoring coral reefs; however, questions have surfaced around the ability of such approaches to capture trends over time. The aim of this study was to develop an approach to assess trends in hard coral cover and evaluate the effectiveness of adaptive designs for estimating such trends in coral reef communities within a region of the Great Barrier Reef. Our approach was couched within a Bayesian design and inference framework such that uncertainty was captured rigorously and so that information from accumulating data can be incorporated straightforwardly to inform future data collection. The designs found under this approach were compared to historical non-adaptive designs which surveyed all locations over time. Through this comparison, we show that adaptive designs can maintain trends over time with little to no loss in information, even when sampling effort is substantially reduced. Accordingly, this research serves to further promote adaptive design methods for efficiently and effectively sampling in ecological monitoring.
期刊介绍:
Environmetrics, the official journal of The International Environmetrics Society (TIES), an Association of the International Statistical Institute, is devoted to the dissemination of high-quality quantitative research in the environmental sciences.
The journal welcomes pertinent and innovative submissions from quantitative disciplines developing new statistical and mathematical techniques, methods, and theories that solve modern environmental problems. Articles must proffer substantive, new statistical or mathematical advances to answer important scientific questions in the environmental sciences, or must develop novel or enhanced statistical methodology with clear applications to environmental science. New methods should be illustrated with recent environmental data.