, Volume 174, Issue 2, pp 559–566 | Cite as

Interactions among resource partitioning, sampling effect, and facilitation on the biodiversity effect: a modeling approach

  • Pedro FlombaumEmail author
  • Osvaldo E. Sala
  • Edward B. Rastetter
Ecosystem ecology - Original research


Resource partitioning, facilitation, and sampling effect are the three mechanisms behind the biodiversity effect, which is depicted usually as the effect of plant-species richness on aboveground net primary production. These mechanisms operate simultaneously but their relative importance and interactions are difficult to unravel experimentally. Thus, niche differentiation and facilitation have been lumped together and separated from the sampling effect. Here, we propose three hypotheses about interactions among the three mechanisms and test them using a simulation model. The model simulated water movement through soil and vegetation, and net primary production mimicking the Patagonian steppe. Using the model, we created grass and shrub monocultures and mixtures, controlled root overlap and grass water-use efficiency (WUE) to simulate gradients of biodiversity, resource partitioning and facilitation. The presence of shrubs facilitated grass growth by increasing its WUE and in turn increased the sampling effect, whereas root overlap (resource partitioning) had, on average, no effect on sampling effect. Interestingly, resource partitioning and facilitation interacted so the effect of facilitation on sampling effect decreased as resource partitioning increased. Sampling effect was enhanced by the difference between the two functional groups in their efficiency in using resources. Morphological and physiological differences make one group outperform the other; once these differences were established further differences did not enhance the sampling effect. In addition, grass WUE and root overlap positively influence the biodiversity effect but showed no interactions.


Resource partitioning Facilitation Sampling effect Patagonian steppe Biodiversity and ecosystem functioning 



We thank Pascal Niklaus and an anonymous reviewer for thorough analysis of our work and suggestions that significantly improved our manuscript; Bonnie L. Kwiatkowski for her assistance in the use of the modeling language; J. B. Hughes Martiny, M. L Yahdjian, M. O. Alexander-Ozinskas, L. G. Reichmann, S. A. Sistla, G. A. Gil, D. D. Correa and L. Vivanco for their comments and feedback during the entire project; and specially M. Bertness who inspired our work. This study was supported by US National Science Foundation DEB 0917668, DEB 1235828, National Academies Keck Futures Initiative 025512, Arizona State University, Marine Biological Lab, the Consejo Nacional de Investigaciones Científicas y Tecnológicas (PIP 11420100100074), and the Agencia Nacional de Promoción Científica y Tecnológica (PICT 1-1-0106).

Supplementary material

442_2013_2775_MOESM1_ESM.pdf (185 kb)
Supplementary material 1 (PDF 185 kb)


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Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  • Pedro Flombaum
    • 1
    • 4
    Email author
  • Osvaldo E. Sala
    • 2
  • Edward B. Rastetter
    • 3
  1. 1.Departamento de Ciencias de la Atmósfera y los Océanos, Centro de Investigaciones del Mar y la Atmósfera, Instituto Franco-Argentino sobre Estudios de Clima y sus Impactos Consejo Nacional de Investigaciones Científicas y Tecnológicas, Universidad de Buenos Aires, Unidad Mixta Internacional (CONICET/UBA-FCEN/UMI-CNRS)Buenos AiresArgentina
  2. 2.School of Life Sciences and School of SustainabilityArizona State UniversityPhoenixUSA
  3. 3.The Ecosystem CenterMarine Biological LaboratoryWoods HoleUSA
  4. 4.Departamento de Ciencias de la Atmósfera y los Océanos (DCAO)Universidad de Buenos AiresBuenos AiresArgentina

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