BIOME3: An equilibrium terrestrial biosphere model based on ecophysiological constraints, resource availability, and competition among plant functional types

Haxeltine, Alex; Prentice, I. Colin

doi:10.1029/96gb02344

Cited by 911 publications

(683 citation statements)

References 49 publications

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“…This explain why paleostudies have used relative simple biogeochemical models. The most popular model was BIOME3 (Haxeltine and Prentice, 1996) or a modified version BIOME4 . It is a process-based terrestrial biosphere model which includes a photosynthesis scheme that simulates acclimation of plants to changed atmospheric CO 2 by optimisation of nitrogen allocation to foliage and by accounting for the effects of CO 2 on net assimilation, stomatal conductance, leaf area index (LAI) and ecosystem water balance.…”

Section: Vegetation Modellingmentioning

confidence: 99%

A few prospective ideas on climate reconstruction: from a statistical single proxy approach towards a multi-proxy and dynamical approach

Guiot

Garreta

et al. 2009

Clim. Past

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Abstract. Important progresses have been made in palaeoclimatological studies by using statistical methods. But they are in somewhere limited as they take the present as an absolute reference. This is particularly true for the modern analogue technique. The availability of mechanistic models to simulate the proxies measured in the sediment cores gives now the possibility to relax this constraint. In particular, vegetation models provide outputs comparable to pollen data (assuming that there is a relationship between plant productivity and pollen counts). The input of such models is, among others, climate. The idea behind paleoclimatological reconstructions is then to obtain inputs, given outputs. This procedure, called model inversion, can be achieved with appropriate algorithms in the frame of the Bayesian statistical theory. But we have chosen to present it in an intuitive way, avoiding the mathematics behind it. Starting from a relative simple application, based on an equilibrium BIOME3 model with a single proxy (pollen), the approach has evolved into two directions: (1) by using several proxies measured on the same core (e.g. lake-level status and δ 13 C) when they are related to a component of the vegetation, and (2) by using a more complex vegetation model, the dynamic vegetation model LPJ-GUESS. Examples presented (most of them being already published) concern Last Glacial Maximum in Europe and Africa, Holocene in a site of the Swiss Jura, anCorrespondence to: J. Guiot (guiot@cerege.fr) Eemian site in France. The main results are that: (1) pollen alone is not able to provide exhaustive information on precipitation, (2) assuming past CO 2 equivalent to modern one may induce biases in climate reconstruction, (3) vegetation models seem to be too much constrained by temperature relative to precipitation in temperate regions. This paper attempts to organise some recent ideas in the palaeoclimatological reconstruction domain and to propose prospectives in that effervescent domain.

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Section: Vegetation Modellingmentioning

confidence: 99%

A few prospective ideas on climate reconstruction: from a statistical single proxy approach towards a multi-proxy and dynamical approach

Guiot

Garreta

et al. 2009

Clim. Past

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“…B (2004) core measurements and atmospheric observations), documented by Sitch et al (2003) was used. Soil texture data were as in BIOME3 (Haxeltine & Prentice (1996a), based on the FAO soil dataset as in Zobler (1986) and FAO (1991)). …”

Section: (C) Baseline Data (I) Climate and Comentioning

confidence: 99%

Tropical forests and the global carbon cycle: impacts of atmospheric carbon dioxide, climate change and rate of deforestation

Crämer

Bondeau

Schaphoff

et al. 2004

Phil. Trans. R. Soc. Lond. B

200

143

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The remaining carbon stocks in wet tropical forests are currently at risk because of anthropogenic deforestation, but also because of the possibility of release driven by climate change. To identify the relative roles of CO 2 increase, changing temperature and rainfall, and deforestation in the future, and the magnitude of their impact on atmospheric CO 2 concentrations, we have applied a dynamic global vegetation model, using multiple scenarios of tropical deforestation (extrapolated from two estimates of current rates) and multiple scenarios of changing climate (derived from four independent offline general circulation model simulations). Results show that deforestation will probably produce large losses of carbon, despite the uncertainty about the deforestation rates. Some climate models produce additional large fluxes due to increased drought stress caused by rising temperature and decreasing rainfall. One climate model, however, produces an additional carbon sink. Taken together, our estimates of additional carbon emissions during the twenty-first century, for all climate and deforestation scenarios, range from 101 to 367 Gt C, resulting in CO 2 concentration increases above background values between 29 and 129 p.p.m. An evaluation of the method indicates that better estimates of tropical carbon sources and sinks require improved assessments of current and future deforestation, and more consistent precipitation scenarios from climate models. Notwithstanding the uncertainties, continued tropical deforestation will most certainly play a very large role in the build-up of future greenhouse gas concentrations.

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“…BIOME4, developed from the BIOME3 model (Haxeltine & Prentice 1996), is a coupled carbon and water flux model that predicts the global steady state of vegetation distribution, structure, and biogeochemistry, taking account of interactions among these aspects.…”

Section: Model Descriptionmentioning

confidence: 99%

Simulated distribution of vegetation types in response to climate change on the Tibetan Plateau

Song

Zhou

Ouyang

2005

J Vegetation Science

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Questions: What is the relationship between alpine vegetation patterns and climate? And how do alpine vegetation patterns respond to climate changes? Location: Tibetan Plateau, southwestern China. The total area is 2 500 000 km 2 with an average altitude over 4000 m. Methods:The geographic distribution of vegetation types on the Tibetan Plateau was simulated based on climatology using a small set of plant functional types (PFTs) embedded in the biogeochemistry-biography model BIOME4. The paleoclimate for the early Holocene was used to explore the possibility of simulating past vegetation patterns. Changes in vegetation patterns were simulated assuming continuous exponential increase in atmospheric CO 2 concentration, based on a transient ocean-atmosphere simulation including sulfate aerosol effects during the 21st century. Results: Forest, shrub steppe, alpine steppe and alpine meadow extended while no desert vegetation developed under the warmer and humid climate of the early Holocene. In the future climate scenario, the simulated tree line is farther north in most sectors than at present. There are also major northward shifts of alpine meadows and a reduction in shrubdominated montane steppe. The boundary between montane desert and alpine desert will be farther to the south than today. The area of alpine desert would decrease, that of montane desert would increase. Conclusions: The outline of changes in vegetation distribution was captured with the simulation. Increased CO2 concentration would potentially lead to big changes in alpine ecosystems.

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BIOME3: An equilibrium terrestrial biosphere model based on ecophysiological constraints, resource availability, and competition among plant functional types

Cited by 911 publications

References 49 publications

A few prospective ideas on climate reconstruction: from a statistical single proxy approach towards a multi-proxy and dynamical approach

A few prospective ideas on climate reconstruction: from a statistical single proxy approach towards a multi-proxy and dynamical approach

Tropical forests and the global carbon cycle: impacts of atmospheric carbon dioxide, climate change and rate of deforestation

Simulated distribution of vegetation types in response to climate change on the Tibetan Plateau

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