The Resource The ecological detective : confronting models with data, Ray Hilborn and Marc Mangel, (electronic resource)

The ecological detective : confronting models with data, Ray Hilborn and Marc Mangel, (electronic resource)

Label
The ecological detective : confronting models with data
Title
The ecological detective
Title remainder
confronting models with data
Statement of responsibility
Ray Hilborn and Marc Mangel
Creator
Contributor
Provider
Subject
Language
eng
Summary
The modern ecologist usually works in both the field and laboratory, uses statistics and computers, and often works with ecological concepts that are model-based, if not model-driven. How do we make the field and laboratory coherent? How do we link models and data? How do we use statistics to help experimentation? How do we integrate modeling and statistics? How do we confront multiple hypotheses with data and assign degrees of belief to different hypotheses? How do we deal with time series (in which data are linked from one measurement to the next) or put multiple sources of data into one
Member of
Cataloging source
E7B
http://library.link/vocab/creatorDate
1947-
http://library.link/vocab/creatorName
Hilborn, Ray
Illustrations
illustrations
Index
index present
LC call number
QH541.15.M3
LC item number
H54 1997eb
Literary form
non fiction
Nature of contents
  • dictionaries
  • bibliography
http://library.link/vocab/relatedWorkOrContributorName
  • Mangel, Marc
  • JSTOR
Series statement
Monographs in population biology
Series volume
28
http://library.link/vocab/subjectName
  • Ecology
  • Ecology
  • Ecology
  • Models
  • SCIENCE
  • Ecology
Label
The ecological detective : confronting models with data, Ray Hilborn and Marc Mangel, (electronic resource)
Instantiates
Publication
Bibliography note
Includes bibliographical references and index
Carrier category
online resource
Carrier category code
  • cr
Carrier MARC source
rdacarrier
Color
multicolored
Content category
text
Content type code
  • txt
Content type MARC source
rdacontent
Contents
  • Cover; MONOGRAPHS IN POPULATION BIOLOGY; Title; Copyright; Dedication; Contents; Preface: Beyond the Null Hypothesis; About the Title; The Audience and Assumed Background; Computer Programming; Realism and Professionalism; Acknowledgments; 1. An Ecological Scenario and the Tools of the Ecological Detective; An Ecological Scenario; The Tools for Ecological Detection; 2. Alternative Views of the Scientific Method and of Modeling; Alternative Views of the Scientific Method; Statistical Inference in Experimental Trees; Unique Aspects of Ecological Data
  • Distinguishing between Models and HypothesesTypes and Uses of Models; Nested Models; Model Complexity; 3. Probability and Probability Models: Know Your Data; Descriptions of Randomness; Always Plot Your Data; Experiments, Events, and Probability; Process and Observation Uncertainties; Some Useful Probability Distributions; The Monte Carlo Method; 4. Incidental Catch in Fisheries: Seabirds in the New Zealand Squid Trawl Fishery; Motivation; The Ecological Setting; ""Statistically Meaningful Data""; The Data; A Negative Binomial Model of By-Catch
  • A Monte Carlo Approach for Estimating the Chance of Success in an Observer ProgramImplications; 5. The Confrontation: Sum of Squares; The Basic Method; Goodness-of-Fit Profiles; Model Selection Using Sum of Squares; 6. The Evolutionary Ecology of Insect Oviposition Behavior; Motivation; The Ecological Setting; The Data; The Models; The Confrontation; Implications; 7. The Confrontation: Likelihood and Maximum Likelihood; Overview; Likelihood and Maximum Likelihood; Determining the Appropriate Likelihood; Model Selection Using Likelihoods; Robustness: Don't Let Outliers Ruin Your Life
  • Bounding the Estimated Parameter: Confidence IntervalsThe Bootstrap Method; Linear Regression, Analysis of Variance, and Maximum Likelihood; 8. Conservation Biology of Wildebeest in the Serengeti; Motivation; The Ecological Setting; The Data; The Models: What Happens When Rainfall Returns to Normal (the 1978 Question)?; The Models: What Is the Intensity of Poaching (the 1992 Question)?; The Confrontation: The Effects of Rainfall; The Confrontation: The Effects of Poaching; Implications; 9. The Confrontation: Bayesian Goodness of Fit; Why Bother with Bayesian Analysis?; Some Examples
  • More Technical ExamplesModel versus Model versus Model; 10. Management of Hake Fisheries in Namibia Motivation; The Impact of Environmental Change; The Ecological Setting; The Data; The Models; The Confrontation; Bayesian Analysis of the LRSG Parameters; Implications; 11. The Confrontation: Understanding How the Best Fit Is Found; Introduction; Direct Search and Graphics; Newton's Method and Gradient Search; Nongradient Methods: Avoiding the Derivative; The Art of Fitting; Hints for Special Problems; Appendix: ""The Method of Multiple Working Hypotheses""; References; Index
Dimensions
unknown
Extent
1 online resource (xvii, 315 pages :)
Form of item
online
Isbn
9781400847310
Media category
computer
Media MARC source
rdamedia
Media type code
  • c
Other physical details
illustrations.
Specific material designation
remote
Stock number
22573/ctt22nbkx
System control number
  • (OCoLC)844328650
  • (OCoLC)ocn844328650
Label
The ecological detective : confronting models with data, Ray Hilborn and Marc Mangel, (electronic resource)
Publication
Bibliography note
Includes bibliographical references and index
Carrier category
online resource
Carrier category code
  • cr
Carrier MARC source
rdacarrier
Color
multicolored
Content category
text
Content type code
  • txt
Content type MARC source
rdacontent
Contents
  • Cover; MONOGRAPHS IN POPULATION BIOLOGY; Title; Copyright; Dedication; Contents; Preface: Beyond the Null Hypothesis; About the Title; The Audience and Assumed Background; Computer Programming; Realism and Professionalism; Acknowledgments; 1. An Ecological Scenario and the Tools of the Ecological Detective; An Ecological Scenario; The Tools for Ecological Detection; 2. Alternative Views of the Scientific Method and of Modeling; Alternative Views of the Scientific Method; Statistical Inference in Experimental Trees; Unique Aspects of Ecological Data
  • Distinguishing between Models and HypothesesTypes and Uses of Models; Nested Models; Model Complexity; 3. Probability and Probability Models: Know Your Data; Descriptions of Randomness; Always Plot Your Data; Experiments, Events, and Probability; Process and Observation Uncertainties; Some Useful Probability Distributions; The Monte Carlo Method; 4. Incidental Catch in Fisheries: Seabirds in the New Zealand Squid Trawl Fishery; Motivation; The Ecological Setting; ""Statistically Meaningful Data""; The Data; A Negative Binomial Model of By-Catch
  • A Monte Carlo Approach for Estimating the Chance of Success in an Observer ProgramImplications; 5. The Confrontation: Sum of Squares; The Basic Method; Goodness-of-Fit Profiles; Model Selection Using Sum of Squares; 6. The Evolutionary Ecology of Insect Oviposition Behavior; Motivation; The Ecological Setting; The Data; The Models; The Confrontation; Implications; 7. The Confrontation: Likelihood and Maximum Likelihood; Overview; Likelihood and Maximum Likelihood; Determining the Appropriate Likelihood; Model Selection Using Likelihoods; Robustness: Don't Let Outliers Ruin Your Life
  • Bounding the Estimated Parameter: Confidence IntervalsThe Bootstrap Method; Linear Regression, Analysis of Variance, and Maximum Likelihood; 8. Conservation Biology of Wildebeest in the Serengeti; Motivation; The Ecological Setting; The Data; The Models: What Happens When Rainfall Returns to Normal (the 1978 Question)?; The Models: What Is the Intensity of Poaching (the 1992 Question)?; The Confrontation: The Effects of Rainfall; The Confrontation: The Effects of Poaching; Implications; 9. The Confrontation: Bayesian Goodness of Fit; Why Bother with Bayesian Analysis?; Some Examples
  • More Technical ExamplesModel versus Model versus Model; 10. Management of Hake Fisheries in Namibia Motivation; The Impact of Environmental Change; The Ecological Setting; The Data; The Models; The Confrontation; Bayesian Analysis of the LRSG Parameters; Implications; 11. The Confrontation: Understanding How the Best Fit Is Found; Introduction; Direct Search and Graphics; Newton's Method and Gradient Search; Nongradient Methods: Avoiding the Derivative; The Art of Fitting; Hints for Special Problems; Appendix: ""The Method of Multiple Working Hypotheses""; References; Index
Dimensions
unknown
Extent
1 online resource (xvii, 315 pages :)
Form of item
online
Isbn
9781400847310
Media category
computer
Media MARC source
rdamedia
Media type code
  • c
Other physical details
illustrations.
Specific material designation
remote
Stock number
22573/ctt22nbkx
System control number
  • (OCoLC)844328650
  • (OCoLC)ocn844328650

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