Long-Term Adjustment of Allocation Parameters in Process-Based Forest Growth Models

1997 ◽  
pp. 293-298
Author(s):  
R. Grote
Keyword(s):  
Growth Models ◽  
Forest Growth ◽  
Forest Growth Models

The Interlinked Mechanisms of Productivity for Developing Process‐Based Forest Growth Models

2021 ◽  
pp. 74-88
Author(s):  
Keshav Tyagi ◽  
Manoj Kumar ◽  
Sweta Nisha Phukon ◽  
Abhishek Ranjan ◽  
Pavan Kumar ◽  
...  
Keyword(s):  
Growth Models ◽  
Forest Growth ◽  
Forest Growth Models

scholarly journals Representation of species mixing in forest growth models. A review and perspective

2015 ◽  
Vol 313 ◽  
pp. 276-292 ◽  
Author(s):  
Hans Pretzsch ◽  
David I. Forrester ◽  
Thomas Rötzer
Keyword(s):  
Growth Models ◽  
Forest Growth ◽  
Forest Growth Models

A framework for uncertainty assessment of mechanistic forest growth models: a neural network example

1997 ◽  
Vol 98 (1) ◽  
pp. 47-58 ◽  
Author(s):  
Biing T. Guan ◽  
George Z. Gertner ◽  
Pablo Parysow
Keyword(s):  
Neural Network ◽  
Growth Models ◽  
Uncertainty Assessment ◽  
Forest Growth ◽  
Forest Growth Models

scholarly journals Volume growth and survival graphs: a method for evaluating process-based forest growth models

2000 ◽  
Vol 20 (5-6) ◽  
pp. 357-365 ◽  
Author(s):  
R. Sievanen ◽  
M. Lindner ◽  
A. Makela ◽  
P. Lasch
Keyword(s):  
Growth Models ◽  
Volume Growth ◽  
Forest Growth ◽  
Growth And Survival ◽  
Forest Growth Models

Modifying Existing Forest Growth Models to Take Account of Effects of Elevated CO2

1992 ◽  
Vol 40 (5) ◽  
pp. 657 ◽  
Author(s):  
RE McMurtrie ◽  
HN Comins ◽  
MUF Kirschbaum ◽  
YP Wang
Keyword(s):  
Nutrient Cycling ◽  
Forest Canopy ◽  
Growth Models ◽  
Forest Growth ◽  
Process Models ◽  
C3 Plants ◽  
Carbon Gain ◽  
Biochemical Basis ◽  
Co2 Effects ◽  
Forest Growth Models

Most published process models of the growth of forest stands are concerned predominantly with either tree physiology or nutrient cycling, concentrating respectively on photosynthetic carbon gain and allocation, or on decomposition and nutrient uptake processes. Mechanistic formulations of direct CO2 effects on photosynthesis have been incorporated in some physiology-based models, whereas modifications incorporating direct CO2 effects in nutrient-driven models have usually been more empirical. Physiology-based models predict considerable CO2-fertiliser effects, while nutrient driven models tend to be less sensitive to elevated ambient CO2 concentration (Ca). This paper describes how effects of elevated Ca can be incorporated in these various types of forest growth models. The magnitude of the simulated response to elevated Ca varies markedly depending on a particular model's spatial and temporal resolution and on which processes are incorporated. Two physiology- based models of forest canopy processes (MAESTRO and BIOMASS) and a plant-soil model (G'DAY) are considered here. MAESTRO and BIOMASS incorporate mechanistic descriptions of the biochemical basis of photosynthesis by C3 plants, while G'DAY contains a simplified formulation but includes soil processes. All three models are used to simulate the response to an instantaneous doubling of Ca. Simulations of MAESTRO and BIOMASS show that on a clear day total canopy photsynthesis is temperature-dependent with increases of approximately 10, 45 and 70% at 10. 25 and 40°C respectively. A simulation for a stand of Pinus radiata growing with abundant water and nutrients and mean annual day-time temperature of 14.8°C shows an increase of 25% in annual canopy photosynthesis. On nutrient-limited sites plant responses to elevated Ca are constrained by feedbacks associated with rates of decomposition and nutrient cycling. According to the G'DAY model, which incorporates these feedbacks, an instantaneous doubling of Ca leads to a 27% initial productivity increase lasting less than a decade and a more modest increase of 8% sustained in the long term.

Evaluation of six process-based forest growth models using eddy-covariance measurements of CO2 and H2 O fluxes at six forest sites in Europe

2002 ◽  
Vol 8 (3) ◽  
pp. 213-230 ◽  
Author(s):  
K. Kramer ◽  
I. Leinonen ◽  
H. H. Bartelink ◽  
P. Berbigier ◽  
M. Borghetti ◽  
...  
Keyword(s):  
Eddy Covariance ◽  
Growth Models ◽  
Forest Growth ◽  
Forest Sites ◽  
Eddy Covariance Measurements ◽  
Forest Growth Models

scholarly journals Prediction Bias Induced by Plot Size in Forest Growth Models

2014 ◽  
Vol 60 (6) ◽  
pp. 1050-1059 ◽  
Author(s):  
Diarietou Sambakhe ◽  
Mathieu Fortin ◽  
Jean-Pierre Renaud ◽  
Christine Deleuze ◽  
Philippe Dreyfus ◽  
...  
Keyword(s):  
Growth Models ◽  
Forest Growth ◽  
Prediction Bias ◽  
Plot Size ◽  
Forest Growth Models
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