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Lessons Learned: Writing a Book on Forest Growth and Yield Modeling
Aaron WeiskittelUniversity of Maine
NEMO
• Oct 1 – 2, 2012
• Penn State University
• Contact Laura Leites or John Kershaw if interested in presenting
Introduction• In 1994, Jerry
Vanclay published a book on growth modeling– Bit outdated
• A few other books on the subject– Compilations or
conference proceedings
– Focused on 1 region– Focused on 1 model
type
IntroductionMeet Jerry
Vanclay in 2006 & inquire about
book
David Hann makes mention
that he will retire soon
John Kershaw mentions that has an existing book contract
Naive young assistant GY
prof arrives at UMaine
Overview• 17 individual chapters
• Covers all aspect of modeling– Development– Application– Verification
• Inclusive of all modeling approaches– Statistical– Mechanistic– Hybrid– Gap
• Research focus, but with foresters and students in mind
• Extensive bibliography
• Improved and logical organization when compared to the first book
• Example models throughout
• Focus on statistical individual tree growth models
Chapter 1 - Introduction
Chapter 1 - Introduction
Chapter 2 - Competition
Both distance-dependent and distance-independent measures discussed
Chapter 3 – Site Productivity
Advantages and disadvantages of various measures of site productivity discussed
Chapter 4 – Whole Stand and Size Class Models
Vanclay’s Original Chapter Updated
Chapter 5 – Individual Tree
Chapter 6 – Components of individual tree models
Diameter increment, height increment, and crown recession
Chapter 7 – Allometric Equations
Height to diameter, height to crown base (crown ratio), crown profile, taper/volume, biomass
Chapter 8 - Mortality
Tree and Stand-level Mortality
Chapter 9 – Regeneration & Recruitment
Seed production, dispersal, and germination; Recruitment models
Chapter 10 – Linking Models of Different Resolutions
Parameter recovery; Disaggregation; Constrained; Combined
Chapter 11 – Forest Management
Genetics, Vegetation Management, Thinning, Fertilization, Harvesting
Chapter 12 – Mechanistic Models
Light interception, Photosynthesis, Stomatal Conductance, Respiration, Carbon Allocation
Chapter 13 – Hybrid Models
Mechanically derived covariates and modifiers
Chapter 14 – Model Construction
Data Requirements; Model form; Parameter estimation
Chapter 15 – Model Evaluation and Calibration
-Model Criticism,
-Model Error Characterization,
-Model Benchmarking
-Bayesian Calibration
Chapter 16 – Implementation and Use
• Collection of Appropriate Data
• Generation of Appropriate Data
• Temporal and Spatial Scale
• Computer Interface
• Visualization
• Output
Chapter 17 – Future Directions
• Improving Predictions
• Improving Input Data
• Improving Software
Summary• Available now via Wiley
• 415 pages with 33 tables, 56 figures, and 1244 citations
• $115 (hardback) and $82 (electronic) on Amazon (cheaper than from Wiley w/ my author’s discount)
Lessons Learned!• Most time-consuming, tedious, and challenging project I have
worked on – Also the most rewarding and enjoyable
• Convincing and keeping co-authors engaged in the project is the biggest accomplishment of my career
• Despite the desire, I don’t see myself completing something like this again due to time and energy constraints
• My big royalty check won’t allow me to retire anytime soon– ~300 copies sold
Acknowledgements
• David Hann
• John Kershaw
• Jerry Vanclay
• Dave Hyink
• Robert Curtis
• Martin Ritchie
• Jeremy Wilson
• Laura Kenefic
• Jeff Gove
• Quang Cao
• Peter Marshall
• Andrew Robinson
Questions/Comments