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Coupling a physiological grazer population model with a generalized model for vegetation dynamics

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  • Pachzelt, Adrian
  • Rammig, Anja
  • Higgins, Steven
  • Hickler, Thomas

Abstract

Large grazers have played a fundamental role in grassland and savannah ecosystems since these vegetation types formed in the late Miocene, but the feedback loops between vegetation and large grazers are still not well understood. Modern dynamic global vegetation models (DGVMs) lack the explicit impact of herbivory, but are calibrated to benchmarks including herbivory. We coupled a generalized model for the population dynamics of large mammalian grazers, based on animal physiology, with a plant-physiological model for vegetation dynamics and ecosystem processes, applicable at local to global scales (LPJ-GUESS). To our knowledge, this is the first attempt to combine process-based grazer population and vegetation modelling in a single generalized modelling framework, applicable at regional to continental scales. The capability of the coupled model to reproduce real-world grazer densities was tested by comparing modelled biomass densities with empirical data from African game parks, where semi-natural grazer populations still exist. The model reproduced inter-park differences in long-term average grazer biomass densities and yielded similar dependencies between major environmental drivers (e.g. precipitation, annual net primary productivity (NPP), dry season length) and grazer population densities as found in other more empirical studies. Amongst the potential environmental drivers, modelled NPP and dry season length were most strongly correlated with empirical and modelled biomass densities. Major discrepancies between modelled and empirical densities occurred for individual parks, but this was expected because the model did not include all factors that influence grazer populations (e.g. nutrient dynamics and poaching). The generalized flexible framework of the coupled model makes it possible to apply the model to other regions, to include further processes (if data for parameterizing them is available) and to parameterize other types of grazers. It could become a useful tool for investigating interactions between grazers and vegetation in a process-based framework.

Suggested Citation

  • Pachzelt, Adrian & Rammig, Anja & Higgins, Steven & Hickler, Thomas, 2013. "Coupling a physiological grazer population model with a generalized model for vegetation dynamics," Ecological Modelling, Elsevier, vol. 263(C), pages 92-102.
    • Handle: RePEc:eee:ecomod:v:263:y:2013:i:c:p:92-102
    DOI: 10.1016/j.ecolmodel.2013.04.025
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    References listed on IDEAS

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    1. Mahesh Sankaran & Niall P. Hanan & Robert J. Scholes & Jayashree Ratnam & David J. Augustine & Brian S. Cade & Jacques Gignoux & Steven I. Higgins & Xavier Le Roux & Fulco Ludwig & Jonas Ardo & Feetha, 2005. "Determinants of woody cover in African savannas," Nature, Nature, vol. 438(7069), pages 846-849, December.
    2. Higgins, Steven I. & Kantelhardt, Jochen & Scheiter, Simon & Boerner, Jan, 2007. "Sustainable management of extensively managed savanna rangelands," Ecological Economics, Elsevier, vol. 62(1), pages 102-114, April.
    3. Hirata, M., 1999. "Modeling digestibility dynamics in leaf segments in a grass: a new approach to forage quality changes in a growing plant," Agricultural Systems, Elsevier, vol. 60(3), pages 169-174, June.
    4. SJ Ryan & CU Knechtel & WM Getz, 2007. "Ecological cues, gestation length, and birth timing in African buffalo (Syncerus caffer)," Behavioral Ecology, International Society for Behavioral Ecology, vol. 18(4), pages 635-644.
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    1. Riggs, Robert A. & Keane, Robert E. & Cimon, Norm & Cook, Rachel & Holsinger, Lisa & Cook, John & DelCurto, Timothy & Baggett, L.Scott & Justice, Donald & Powell, David & Vavra, Martin & Naylor, Bridg, 2015. "Biomass and fire dynamics in a temperate forest-grassland mosaic: Integrating multi-species herbivory, climate, and fire with the FireBGCv2/GrazeBGC system," Ecological Modelling, Elsevier, vol. 296(C), pages 57-78.

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