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Tree mortality in dynamic vegetation models – A key feature for accurately simulating forest properties

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  • Manusch, Corina
  • Bugmann, Harald
  • Heiri, Caroline
  • Wolf, Annett

Abstract

Dynamic vegetation models are important tools in ecological research, but not all processes of vegetation dynamics are captured adequately. Tree mortality is often modeled as a function of growth efficiency and maximum age. However, empirical studies have shown for different species that slow-growing trees may become older than fast-growing trees, implying a correlation of mortality with growth rate and size rather than age. We used the ecosystem model LPJ-GUESS to compare the standard age-dependent mortality with two size-dependent mortality approaches. We found that all mortality approaches, when calibrated, yield a realistic pattern of growing stock and Plant Functional Type (PFT) distribution at five study sites in Switzerland. However, only the size-dependent approaches match a third pattern, i.e. the observed negative relationship between growth rate and longevity. As a consequence, trees are simulated to get older at higher than at lower altitudes/latitudes. In contrast, maximum tree ages do not change along these climatic gradients when the standard age-dependent mortality is used. As tree age and size determine forest structure, our more realistic mortality assumptions improved forest biomass estimation, but indicate a potential decline of carbon storage under climate change. We conclude that tree mortality should be modeled as a function of size rather than age.

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  • Manusch, Corina & Bugmann, Harald & Heiri, Caroline & Wolf, Annett, 2012. "Tree mortality in dynamic vegetation models – A key feature for accurately simulating forest properties," Ecological Modelling, Elsevier, vol. 243(C), pages 101-111.
  • Handle: RePEc:eee:ecomod:v:243:y:2012:i:c:p:101-111
    DOI: 10.1016/j.ecolmodel.2012.06.008
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    References listed on IDEAS

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    1. Wolf, Annett, 2011. "Estimating the potential impact of vegetation on the water cycle requires accurate soil water parameter estimation," Ecological Modelling, Elsevier, vol. 222(15), pages 2595-2605.
    2. Peter M. Cox & Richard A. Betts & Chris D. Jones & Steven A. Spall & Ian J. Totterdell, 2000. "Acceleration of global warming due to carbon-cycle feedbacks in a coupled climate model," Nature, Nature, vol. 408(6809), pages 184-187, November.
    3. David C. Frank & Jan Esper & Christoph C. Raible & Ulf Büntgen & Valerie Trouet & Benjamin Stocker & Fortunat Joos, 2010. "Ensemble reconstruction constraints on the global carbon cycle sensitivity to climate," Nature, Nature, vol. 463(7280), pages 527-530, January.
    4. Wramneby, Anna & Smith, Benjamin & Zaehle, Sönke & Sykes, Martin T., 2008. "Parameter uncertainties in the modelling of vegetation dynamics—Effects on tree community structure and ecosystem functioning in European forest biomes," Ecological Modelling, Elsevier, vol. 216(3), pages 277-290.
    5. Peter M. Cox & Richard A. Betts & Chris D. Jones & Steven A. Spall & Ian J. Totterdell, 2000. "Erratum: Acceleration of global warming due to carbon-cycle feedbacks in a coupled climate model," Nature, Nature, vol. 408(6813), pages 750-750, December.
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    1. Roessiger, Joerg & Griess, Verena C. & Härtl, Fabian & Clasen, Christian & Knoke, Thomas, 2013. "How economic performance of a stand increases due to decreased failure risk associated with the admixing of species," Ecological Modelling, Elsevier, vol. 255(C), pages 58-69.
    2. Manusch, Corina & Bugmann, Harald & Wolf, Annett, 2014. "Sensitivity of simulated productivity to soil characteristics and plant water uptake along drought gradients in the Swiss Alps," Ecological Modelling, Elsevier, vol. 282(C), pages 25-34.

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