scholarly journals Global vegetation distribution driving factors in two Dynamic Global Vegetation Models of contrasting complexities

2019 ◽  
Vol 180 ◽  
pp. 51-65 ◽  
Author(s):  
Huan Li ◽  
Hans Renssen ◽  
Didier M. Roche
Keyword(s):  
Driving Factors ◽  
Vegetation Distribution ◽  
Dynamic Global Vegetation Models ◽  
Vegetation Models ◽  
Global Vegetation

scholarly journals Calibration of the maximum carboxylation velocity (Vcmax) using data mining techniques and ecophysiological data from the Brazilian semiarid region, for use in Dynamic Global Vegetation Models

2016 ◽  
Vol 76 (2) ◽  
pp. 341-351
Author(s):  
L. F. C. Rezende ◽  
B. C. Arenque-Musa ◽  
M. S. B. Moura ◽  
S. T. Aidar ◽  
C. Von Randow ◽  
...  
Keyword(s):  
Data Mining ◽  
Native Species ◽  
Classification And Regression Tree ◽  
Northeastern Brazil ◽  
Semiarid Region ◽  
Global Changes ◽  
Data Mining Techniques ◽  
Dynamic Global Vegetation Models ◽  
Vegetation Models ◽  
Global Vegetation

Abstract The semiarid region of northeastern Brazil, the Caatinga, is extremely important due to its biodiversity and endemism. Measurements of plant physiology are crucial to the calibration of Dynamic Global Vegetation Models (DGVMs) that are currently used to simulate the responses of vegetation in face of global changes. In a field work realized in an area of preserved Caatinga forest located in Petrolina, Pernambuco, measurements of carbon assimilation (in response to light and CO2) were performed on 11 individuals of Poincianella microphylla, a native species that is abundant in this region. These data were used to calibrate the maximum carboxylation velocity (Vcmax) used in the INLAND model. The calibration techniques used were Multiple Linear Regression (MLR), and data mining techniques as the Classification And Regression Tree (CART) and K-MEANS. The results were compared to the UNCALIBRATED model. It was found that simulated Gross Primary Productivity (GPP) reached 72% of observed GPP when using the calibrated Vcmax values, whereas the UNCALIBRATED approach accounted for 42% of observed GPP. Thus, this work shows the benefits of calibrating DGVMs using field ecophysiological measurements, especially in areas where field data is scarce or non-existent, such as in the Caatinga.

scholarly journals Modelling tropical forest responses to drought and El Niño with a stomatal optimization model based on xylem hydraulics

2018 ◽  
Vol 373 (1760) ◽  
pp. 20170315 ◽  
Author(s):  
Cleiton B. Eller ◽  
Lucy Rowland ◽  
Rafael S. Oliveira ◽  
Paulo R. L. Bittencourt ◽  
Fernanda V. Barros ◽  
...  
Keyword(s):  
Tropical Forest ◽  
El Niño ◽  
Optimization Model ◽  
El Nino ◽  
Soil Drought ◽  
Forest Sites ◽  
Dynamic Global Vegetation Models ◽  
Vegetation Models ◽  
Global Vegetation

The current generation of dynamic global vegetation models (DGVMs) lacks a mechanistic representation of vegetation responses to soil drought, impairing their ability to accurately predict Earth system responses to future climate scenarios and climatic anomalies, such as El Niño events. We propose a simple numerical approach to model plant responses to drought coupling stomatal optimality theory and plant hydraulics that can be used in dynamic global vegetation models (DGVMs). The model is validated against stand-scale forest transpiration ( E ) observations from a long-term soil drought experiment and used to predict the response of three Amazonian forest sites to climatic anomalies during the twentieth century. We show that our stomatal optimization model produces realistic stomatal responses to environmental conditions and can accurately simulate how tropical forest E responds to seasonal, and even long-term soil drought. Our model predicts a stronger cumulative effect of climatic anomalies in Amazon forest sites exposed to soil drought during El Niño years than can be captured by alternative empirical drought representation schemes. The contrasting responses between our model and empirical drought factors highlight the utility of hydraulically-based stomatal optimization models to represent vegetation responses to drought and climatic anomalies in DGVMs. This article is part of a discussion meeting issue ‘The impact of the 2015/2016 El Niño on the terrestrial tropical carbon cycle: patterns, mechanisms and implications’.

scholarly journals Fractal properties of forest fires in Amazonia as a basis for modelling pan-tropical burnt area

2014 ◽  
Vol 11 (6) ◽  
pp. 1449-1459 ◽  
Author(s):  
I. N. Fletcher ◽  
L. E. O. C. Aragão ◽  
A. Lima ◽  
Y. Shimabukuro ◽  
P. Friedlingstein
Keyword(s):  
Forest Fires ◽  
Large Scale ◽  
Fire Spread ◽  
Small Scale ◽  
Burnt Area ◽  
Active Fire ◽  
Fractal Properties ◽  
Dynamic Global Vegetation Models ◽  
Vegetation Models ◽  
Global Vegetation

Abstract. Current methods for modelling burnt area in dynamic global vegetation models (DGVMs) involve complex fire spread calculations, which rely on many inputs, including fuel characteristics, wind speed and countless parameters. They are therefore susceptible to large uncertainties through error propagation, but undeniably useful for modelling specific, small-scale burns. Using observed fractal distributions of fire scars in Brazilian Amazonia in 2005, we propose an alternative burnt area model for tropical forests, with fire counts as sole input and few parameters. This model is intended for predicting large-scale burnt area rather than looking at individual fire events. A simple parameterization of a tapered fractal distribution is calibrated at multiple spatial resolutions using a satellite-derived burnt area map. The model is capable of accurately reproducing the total area burnt (16 387 km2) and its spatial distribution. When tested pan-tropically using the MODIS MCD14ML active fire product, the model accurately predicts temporal and spatial fire trends, but the magnitude of the differences between these estimates and the GFED3.1 burnt area products varies per continent.

Where is the carbon going? - A multi-model comparison

2021 ◽  
Author(s):  
Michael O'Sullivan ◽  
Pierre Friedlingstein ◽  
Stephen Sitch
Keyword(s):  
Model Comparison ◽  
Net Primary Productivity ◽  
Relative Increase ◽  
Historical Period ◽  
Residence Times ◽  
Vegetation Carbon ◽  
Dynamic Global Vegetation Models ◽  
Spatio Temporal ◽  
Vegetation Models ◽  
Global Vegetation

<p>Net terrestrial carbon uptake is primarily driven by increases in net primary productivity (NPP) and/or the residence time of carbon in vegetation and soil. As such, it is of critical importance to accurately quantify spatio-temporal variation in both terms and determine their drivers. Both NPP and residence times are modulated by changing environmental conditions, including climate change and variability, atmospheric CO<sub>2</sub>, and Land Use and Land Cover Changes (LULCC). For the historical period, 1901-2019, outputs from a suite of Dynamic Global Vegetation Models (DGVMs) from the TRENDY consortium, driven with observed changes in climate, CO<sub>2</sub>, and LULCC are analysed. Changes in global and regional carbon fluxes, stocks, and residence times are quantified, as well as an attribution to the underlying drivers. We find that over the historical period the majority of models simulate an increase in NPP, predominantly driven by enhanced atmospheric CO<sub>2</sub> concentrations. This generally leads to increased carbon storage in both vegetation and soils, however there is no agreement across models on the partitioning between vegetation and soils. This increased storage also acts to reduce soil carbon residence times due to a relative increase in carbon allocated in the faster decomposing soil pools. LULCC over this period has acted to reduce carbon inputs to the system and reduce vegetation carbon residence times due to conversion of forests to shorter vegetation. We find there is a large variation in simulated global and regional fluxes, stocks, and residence times in resonse to changes in climate, implying there are considerable uncertainties in current DGVMs. We therefore use long-term global observations of productivity and biomass change to constrain model estimates and provide insight into a process attribution for biospheric change as well as highlighting areas for future model improvement.</p>

Dynamic Global Vegetation Models

Plant Ecology ◽  
2018 ◽  
pp. 843-863
Author(s):  
Ernst-Detlef Schulze ◽  
Erwin Beck ◽  
Nina Buchmann ◽  
Stephan Clemens ◽  
Klaus Müller-Hohenstein ◽  
...  
Keyword(s):  
Dynamic Global Vegetation Models ◽  
Vegetation Models ◽  
Global Vegetation

Using Dynamic Global Vegetation Models (DGVMs) for Projecting Ecosystem Services at Regional Scales

2019 ◽  
pp. 57-61
Author(s):  
Alice Boit ◽  
Boris Sakschewski ◽  
Lena Boysen ◽  
Ana Cano-Crespo ◽  
Jan Clement ◽  
...  
Keyword(s):  
Ecosystem Services ◽  
Dynamic Global Vegetation Models ◽  
Vegetation Models ◽  
Global Vegetation

Simulating Competition and Coexistence between Plant Functional Types in a Dynamic Vegetation Model

2006 ◽  
Vol 10 (10) ◽  
pp. 1-30 ◽  
Author(s):  
Vivek K. Arora ◽  
George J. Boer
Keyword(s):  
Terrestrial Ecosystem ◽  
Ecosystem Model ◽  
Plant Functional Types ◽  
Quasi Equilibrium ◽  
Terrestrial Ecosystem Model ◽  
Functional Types ◽  
Dynamic Global Vegetation Models ◽  
Vegetation Models ◽  
Competition Equations ◽  
Global Vegetation

Abstract The global distribution of vegetation is broadly determined by climate, and where bioclimatic parameters are favorable for several plant functional types (PFTs), by the competition between them. Most current dynamic global vegetation models (DGVMs) do not, however, explicitly simulate inter-PFT competition and instead determine the existence and fractional coverage of PFTs based on quasi-equilibrium climate–vegetation relationships. When competition is explicitly simulated, versions of Lotka–Volterra (LV) equations developed in the context of interaction between animal species are almost always used. These equations may, however, exhibit unrealistic behavior in some cases and do not, for example, allow the coexistence of different PFTs in equilibrium situations. Coexistence may, however, be obtained by introducing features and mechanisms such as temporal environmental variation and disturbance, among others. A generalized version of the competition equations is proposed that includes the LV equations as a special case, which successfully models competition for a range of climate and vegetation regimes and for which coexistence is a permissible equilibrium solution in the absence of additional mechanisms. The approach is tested for boreal forest, tropical forest, savanna, and temperate forest locations within the framework of the Canadian Terrestrial Ecosystem Model (CTEM) and successfully simulates the observed successional behavior and the observed near-equilibrium distribution of coexisting PFTs.

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