A Wood Biology Agenda to Support Global Vegetation Modelling. (November 2018)
- Record Type:
- Journal Article
- Title:
- A Wood Biology Agenda to Support Global Vegetation Modelling. (November 2018)
- Main Title:
- A Wood Biology Agenda to Support Global Vegetation Modelling
- Authors:
- Zuidema, Pieter A.
Poulter, Benjamin
Frank, David C. - Abstract:
- Abstract : Realistic forecasting of forest responses to climate change critically depends on key advancements in global vegetation modelling. Compared with traditional 'big-leaf' models that simulate forest stands, 'next-generation' vegetation models aim to track carbon-, light-, water-, and nutrient-limited growth of individual trees. Wood biology can play an important role in delivering the required knowledge at tissue-to-individual levels, at minute-to-century scales and for model parameterization and benchmarking. We propose a wood biology research agenda that contributes to filling six knowledge gaps: sink versus source limitation, drivers of intra-annual growth, drought impacts, functional wood traits, dynamic biomass allocation, and nutrient cycling. Executing this agenda will expedite model development and increase the ability of models to forecast global change impact on forest dynamics. Highlights: 'Next-generation' global vegetation models track the performance of individual trees as a function of light, carbon, water, and nutrient availability, explicitly include forest demography, and simulate disturbances. This model development involves a major increase in complexity and in the amount of simulated processes. The development and quality of next-generation models critically depends on the availability of insights to simulate these additional processes. Yet, knowledge on key processes such as sub-annual tree growth, source- versus sink-limited growth, dynamicAbstract : Realistic forecasting of forest responses to climate change critically depends on key advancements in global vegetation modelling. Compared with traditional 'big-leaf' models that simulate forest stands, 'next-generation' vegetation models aim to track carbon-, light-, water-, and nutrient-limited growth of individual trees. Wood biology can play an important role in delivering the required knowledge at tissue-to-individual levels, at minute-to-century scales and for model parameterization and benchmarking. We propose a wood biology research agenda that contributes to filling six knowledge gaps: sink versus source limitation, drivers of intra-annual growth, drought impacts, functional wood traits, dynamic biomass allocation, and nutrient cycling. Executing this agenda will expedite model development and increase the ability of models to forecast global change impact on forest dynamics. Highlights: 'Next-generation' global vegetation models track the performance of individual trees as a function of light, carbon, water, and nutrient availability, explicitly include forest demography, and simulate disturbances. This model development involves a major increase in complexity and in the amount of simulated processes. The development and quality of next-generation models critically depends on the availability of insights to simulate these additional processes. Yet, knowledge on key processes such as sub-annual tree growth, source- versus sink-limited growth, dynamic biomass allocation, drought effects, and nutrient cycling is currently poorly available. Wood biology can importantly contribute to filling this knowledge gap by providing knowledge on crucial processes for tree functioning. This field of science is well positioned due to recent progress in concepts, measuring tools, and analyses. … (more)
- Is Part Of:
- Trends in plant science. Volume 23:Number 11(2018)
- Journal:
- Trends in plant science
- Issue:
- Volume 23:Number 11(2018)
- Issue Display:
- Volume 23, Issue 11 (2018)
- Year:
- 2018
- Volume:
- 23
- Issue:
- 11
- Issue Sort Value:
- 2018-0023-0011-0000
- Page Start:
- 1006
- Page End:
- 1015
- Publication Date:
- 2018-11
- Subjects:
- Climate change -- Earth system models -- individual-based models -- forests -- vegetation modelling
Botany -- Periodicals
Botanique -- Périodiques
Botany
Periodicals
580.5 - Journal URLs:
- http://www.sciencedirect.com/science/journal/13601385 ↗
http://www.elsevier.com/journals ↗ - DOI:
- 10.1016/j.tplants.2018.08.003 ↗
- Languages:
- English
- ISSNs:
- 1360-1385
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - 9049.675450
British Library DSC - BLDSS-3PM
British Library HMNTS - ELD Digital store - Ingest File:
- 8351.xml