Introduction to Quantitative Ecology
Introduction to Quantitative Ecology

Author: Timothy E. Essington

Publisher: Oxford University Press

Published: 2021

Total Pages: 321

ISBN-13: 0192843478

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Environmental science (ecology, conservation, and resource management) is an increasingly quantitative field. A well-trained ecologist now needs to evaluate evidence generated from complex quantitative methods, and to apply these methods in their own research. Yet the existing books and academic coursework are not adequately serving most of the potential audience - instead they cater to the specialists who wish to focus on either mathematical or statistical aspects, and overwhelmingly appeal to those who already have confidence in their quantitative skills. At the same time, many texts lack an explicit emphasis on the epistemology of quantitative techniques. That is, how do we gain understanding about the real world from models that are so vastly simplified? This accessible textbook introduces quantitative ecology in a manner that aims to confront these limitations and thereby appeal to a far wider audience. It presents material in an informal, approachable, and encouraging manner that welcomes readers with any degree of confidence and prior training. It covers foundational topics in both mathematical and statistical ecology before describing how to implement these concepts to choose, use, and analyse models, providing guidance and worked examples in both spreadsheet format and R. The emphasis throughout is on the skilful interpretation of models to answer questions about the natural world. Introduction to Quantitative Ecology is suitable for advanced undergraduate students and incoming graduate students, seeking to strengthen their understanding of quantitative methods and to apply them successfully to real world ecology, conservation, and resource management scenarios.

Quantitative Ecological Theory
Quantitative Ecological Theory

Author: M.R. Rose

Publisher: Springer Science & Business Media

Published: 2012-12-06

Total Pages: 213

ISBN-13: 9401165610

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This is an inadvertent book, though it did arise naturally enough from a course I give in theoretical ecology. But I wouldn't have given the course at all if one colleague in my department hadn't left for a leave of absence, while another abruptly resigned. This propelled me to the fore where this teaching responsibility was concerned, one I had never had any intention of discharging. Then it turned out that one of my students was regularly unable to make half the classes. As a result, I began giving him my lecture notes each week. As I knew that someone else would be reading them, I began to write my notes more carefully. Naturally enough, the other students soon began to demand the notes too. Eventually they were indulged. Thus I found myself writing a textbook manuscript. By the next year, the students were handed all their notes in one package at the outset. But these were still just hand-written. Inevitably, the demand that they be typed arose. This I didn't want to do until I found a publisher. As it turned out, Tim Hardwick of Croom Helm was willing to have his firm fill this role, to my great satisfaction. • and his considerable frustration. I have been a desultory author about producing this final text, and can only express my gratitude for his enduring patience over more than 18 months of delays.

Ecological Forecasting
Ecological Forecasting

Author: Michael C. Dietze

Publisher: Princeton University Press

Published: 2017-05-30

Total Pages: 285

ISBN-13: 1400885450

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An authoritative and accessible introduction to the concepts and tools needed to make ecology a more predictive science Ecologists are being asked to respond to unprecedented environmental challenges. How can they provide the best available scientific information about what will happen in the future? Ecological Forecasting is the first book to bring together the concepts and tools needed to make ecology a more predictive science. Ecological Forecasting presents a new way of doing ecology. A closer connection between data and models can help us to project our current understanding of ecological processes into new places and times. This accessible and comprehensive book covers a wealth of topics, including Bayesian calibration and the complexities of real-world data; uncertainty quantification, partitioning, propagation, and analysis; feedbacks from models to measurements; state-space models and data fusion; iterative forecasting and the forecast cycle; and decision support. Features case studies that highlight the advances and opportunities in forecasting across a range of ecological subdisciplines, such as epidemiology, fisheries, endangered species, biodiversity, and the carbon cycle Presents a probabilistic approach to prediction and iteratively updating forecasts based on new data Describes statistical and informatics tools for bringing models and data together, with emphasis on: Quantifying and partitioning uncertainties Dealing with the complexities of real-world data Feedbacks to identifying data needs, improving models, and decision support Numerous hands-on activities in R available online