Før Memmo var notatene mine spredt overalt i PDF-er. Nå samler et arbeidsområde alt på ett sted – jeg ser akkurat hva som gjenstår å studere.
Fisheries science is an applied field. A biologist working on a depleted population might need to forecast the population trajectory or examine which factors are limiting recovery. For an exploited population, a biologist might investigate whether the fishery or the stock would be improved through harvest regulation, such as a quota or size limit. Addressing those sorts of questions generally involves estimating parameters such as population size or survival rate. An essential step is characterizing the degree of uncertainty in results, which can be substantial for fisheries models. Bayesian methods and current software provide a flexible and powerful framework for addressing these challenges. Models developed using Bayesian software can be tailored to the unique aspects of each field study.
A Bayesian Introduction to Fish Population Analysis is aimed at advanced undergraduate and graduate students as well as working professionals interested in a hands-on introduction to Bayesian approaches for fitting fisheries models. Chapters address key aspects of population dynamics: abundance, mortality, growth, and recruitment. The book includes complete R code for simulating each study design and JAGS Bayesian code for model fitting; code files are also available online. No prior knowledge of R or JAGS is assumed and new commands are introduced gradually through the sequence of examples. There is emphasis throughout the book on how to vary simulation settings to develop intuition about fisheries models (e.g., how many fish should be tagged in order to obtain usefully precise results). Additional topics include development of integrated population models, model checking, model selection, and uninformative and informative prior distributions.
Key features include:
Joseph E. Hightower is a professor emeritus in the Department of Applied Ecology at NC
State University. His research interests focus on fish population dynamics, especially field and
analytical methods for estimating population parameters. His primary teaching role was a
graduate course in quantitative fisheries management, including Bayesian methods that serve
as the foundation for this book.
Før Memmo var notatene mine spredt overalt i PDF-er. Nå samler et arbeidsområde alt på ett sted – jeg ser akkurat hva som gjenstår å studere.
Memmos sammendrag er gull før eksamen. Jeg slipper å lese 800 sider to uker før – bare det viktigste.
AI-chatten har reddet meg kvelden før eksamen mer enn én gang. Jeg bare spør til jeg forstår – slipper å vente på svar i en studiegruppe.
Quizene treffer akkurat det jeg trenger å vite. Memmo holder styr på hva jeg sliter med – så jeg øver bare på det som er verdt det.
Flashcards med repetisjon over tid er magi. Memmo vet når jeg er i ferd med å glemme noe og viser det igjen.
AI-podkastene er min favoritt. Jeg lytter på vei til skolen og får en repetisjon uten å sitte foran en datamaskin.
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