Bayesian Applications in Environmental and Ecological Studies with R and Stan

Modern ecological and environmental sciences are dominated by observational data. As a result, traditional statistical training often leaves scientists ill-prepared for the data analysis tasks they encounter in their work. Bayesian methods provide a more robust and flexible tool for data analysis, as they enable information from different sources to be brought into the modelling process. Bayesian Applications in Evnironmental and Ecological Studies with R and Stan provides a Bayesian framework for model formulation, parameter estimation, and model evaluation in the context of analyzing environmental and ecological data.

Features
- An accessible overview of Bayesian methods in environmental and ecological studies
- Emphasizes the hypothetical deductive process, particularly model formulation
- Necessary background material on Bayesian inference and Monte Carlo simulation
- Detailed case studies, covering water quality monitoring and assessment, ecosystem response to urbanization, fisheries ecology, and more
- Advanced chapter on Bayesian applications, including Bayesian networks and a change point model
- Complete code for all examples, along with the data used in the book, are available via GitHub

The book is primarily aimed at graduate students and researchers in the environmental and ecological sciences, as well as environmental management professionals. This is a group of people representing diverse subject matter fields, who could benefit from the potential power and flexibility of Bayesian methods.

現代生態與環境科學主要依賴觀察數據。因此，傳統的統計培訓往往使科學家在工作中遇到的數據分析任務措手不及。貝葉斯方法提供了一種更強大和靈活的數據分析工具，因為它們可以將來自不同來源的信息納入建模過程中。《R和Stan在環境和生態研究中的貝葉斯應用》提供了一個貝葉斯框架，用於在分析環境和生態數據的背景下進行模型制定、參數估計和模型評估。

特點：
- 對環境和生態研究中的貝葉斯方法進行易於理解的概述
- 強調假設演繹過程，特別是模型制定
- 關於貝葉斯推斷和蒙特卡羅模擬的必要背景材料
- 詳細的案例研究，包括水質監測和評估、生態系統對城市化的反應、漁業生態學等
- 進階章節介紹貝葉斯應用，包括貝葉斯網絡和變點模型
- 所有示例的完整代碼以及書中使用的數據可通過GitHub獲取

本書主要針對環境和生態科學的研究生和研究人員，以及環境管理專業人士。這是一個代表不同學科領域的人群，他們可以從貝葉斯方法的潛在威力和靈活性中受益。

Song S. Qian is a professor at The University of Toledo, Department of Environmental Sciences. He earned a PhD in environmental sciences and an MS in statistics from Duke University. He has worked in both environmental consulting and academia for more than 25 years. His work is focused on the application of statistics in environmental and ecological data analysis and modeling. His publication of such applications cover a wide range of topics, including wetland nutrient retention, lake eutrophication, water quality compliance assessment, drinking water safety, fisheries management, effects of climate change, and quantitative chemistry. He has taught graduate-level applied statistics to students in environmental science and ecology for 25 years. He authored and co-authored more than 115 research papers in peer-reviewed journals and a book in environmental and ecological statistics (currently in its second edition).

Mark R. DuFour earned a PhD in biology with a focus in ecology from The University of Toledo. He has worked in the fisheries field for more than 15 years, including periods with the New York State Department of Environmental Conservation and Ohio Department of Natural Resources. He is currently a fisheries biologist with the U.S. Geological Survey - Great Lakes Science Center. Dr. DuFour focuses on the quantitative aspects of fisheries science, seeks opportunities to apply Bayesian hierarchical modeling, and has contributed to 23 peer-reviewed publications. His quantitative training includes a combination of course work, diligent advisement, and on-the-job training through application. In contributing to this book, he hopes to encourage other science practitioners to look behind the statistical analysis curtain when developing ecological and environmental models.

Ibrahim Alameddine is an associate professor at the American University of Beirut, Department of Civil and Environmental Engineering. He earned his PhD in environmental sciences from Duke University. His research interests focus on advancing environmental monitoring and assessment, particularly in freshwater systems suffering from anthropogenic eutrophication and harmful algal blooms. His work concentrates on advancing the use of statistics for the effective monitoring, modeling, and management of environmental systems. Dr. Alameddine has taught several graduate courses on environmental statistics, water quality modeling, and geospatial analysis. He has published more than 60 peer-reviewed manuscripts and scientific reports. In addition to his academic position, he serves as a consultant to several local and regional governmental bodies as well as international organizations working in the environmental field.

宋 S. 錢是托萊多大學環境科學系的教授。他在杜克大學獲得了環境科學博士學位和統計學碩士學位。他在環境諮詢和學術界工作超過25年。他的工作專注於統計在環境和生態數據分析和建模中的應用。他發表的應用涵蓋了廣泛的主題，包括濕地營養物保留、湖泊優養化、水質合規評估、飲用水安全、漁業管理、氣候變化影響和定量化學等。他已經教授環境科學和生態學研究生應用統計學25年。他在同行評審期刊上撰寫和合著了115篇以上的研究論文，並撰寫了一本環境和生態統計學的書籍（目前第二版）。

馬克 R. 杜福爾在托萊多大學獲得了生物學博士學位，專攻生態學。他在漁業領域工作超過15年，包括在紐約州環境保護部和俄亥俄州自然資源部的工作。他目前是美國地質調查局 - 大湖科學中心的漁業生物學家。杜福爾博士專注於漁業科學的定量方面，尋求應用貝葉斯階層建模的機會，並為23篇同行評審的出版物做出了貢獻。他的定量培訓包括課程學習、專業指導和實際應用的在職培訓。他希望通過參與本書的撰寫，鼓勵其他科學從業者在開發生態和環境模型時深入研究統計分析。

易卜拉欣·阿拉梅丁是貝魯特美國大學土木與環境工程系的副教授。他在杜克大學獲得了環境科學博士學位。他的研究興趣集中在推進環境監測和評估，特別是在受人為優養化和有害藻類水體中。他的工作集中於推進統計在環境系統的有效監測、建模和管理中的應用。阿拉梅丁博士教授了幾門研究生課程，包括環境統計學、水質建模和地理空間分析。他發表了60多篇同行評審的論文和科學報告。除了學術職位外，他還擔任多個地方和區域政府機構以及在環境領域工作的國際組織的顧問。