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Use of Spatial Analysis to Test Hypotheses on Plant Recruitment in a Hyper-Arid Ecosystem

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  • Jan J Quets
  • Stijn Temmerman
  • Magdy I El-Bana
  • Saud L Al-Rowaily
  • Abdulaziz M Assaeed
  • Ivan Nijs

Abstract

Mounds originating from wind-blown sediment accumulation beneath vegetation (nebkhas) often indicate land degradation in dry areas. Thus far, most nebkha research has focused on individual plants. Here, we aimed to explore population-scale processes (up to scales of about 100 m) that might explain an observed nebkha landscape pattern. We mapped the Rhazya stricta Decne. population in a 3 ha study site in a hyper-arid region of Saudi Arabia. We compared the spatial patterns of five different cohorts (age classes) of observed nebkha host plants to those expected under several hypothesized drivers of recruitment and intraspecific interaction. We found that all R. stricta cohorts had a limited fractional vegetation cover and established in large-scale clusters. This clustering weakened with cohort age, possibly indicating merging of neighboring vegetation patches. Different cohort clusters did not spatially overlap in most cases, indicating that recruitment patterns changed position over time. Strong indications were found that the main drivers underlying R. stricta spatial configurations were allogenic (i.e. not driven by vegetation) and dynamic. Most likely these drivers were aeolian-driven sand movement or human disturbance which forced offspring recruitment in spatially dynamic clusters. Competition and facilitation were likely active on the field site too, but apparently had a limited effect on the overall landscape structure.

Suggested Citation

  • Jan J Quets & Stijn Temmerman & Magdy I El-Bana & Saud L Al-Rowaily & Abdulaziz M Assaeed & Ivan Nijs, 2014. "Use of Spatial Analysis to Test Hypotheses on Plant Recruitment in a Hyper-Arid Ecosystem," PLOS ONE, Public Library of Science, vol. 9(3), pages 1-11, March.
  • Handle: RePEc:plo:pone00:0091184
    DOI: 10.1371/journal.pone.0091184
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    References listed on IDEAS

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    1. Baddeley, Adrian & Turner, Rolf, 2005. "spatstat: An R Package for Analyzing Spatial Point Patterns," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 12(i06).
    2. Bo Wu & Hongxiao Yang, 2013. "Spatial Patterns and Natural Recruitment of Native Shrubs in a Semi-arid Sandy Land," PLOS ONE, Public Library of Science, vol. 8(3), pages 1-10, March.
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