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Community Ecology

, Volume 2, Issue 2, pp 221–230 | Cite as

Detection of fine-scale relationships between species composition and biomass in grassland

  • M. KertészEmail author
  • B. Lhotsky
  • I. Hahn
Article

Abstract

We elaborated and tested a novel operative framework for sampling and analysing fine-scale pattern of plant composition and biomass. We combined presence/absence sampling of plant species with non-destructive biomass estimation. In an open perennial sand grassland, we used 46 m long circular transects consisting of 0.05 m by 0.05 m adjoining elementary sampling units. This arrangement allows us to scale across a range of 0.05 to 20 m. For measuring aboveground green biomass, we applied digital camera sensitive to red and near infrared parts of light spectrum, and we calculated normalised differential vegetation index (NDVI). We used information statistics proposed by Juhász-Nagy to study the association between spatial patterns of production and species composition. Since information statistical functions applied require binary data, we transformed NDVI data into one or several binary variables. We found that not only dominant species but subordinate gap species were also associated to high biomass, although the strength of association varied across scales. Most of the significant associations were detected at fine scales, from 0.05 to 0.25 m. At the scales commensurable with quadrat sizes usually applied in grasslands, i.e., from 0.5 to 2.0 m, we could hardly find any significant associations between species composition and biomass. We concluded that the novel methods applied proved reliable for studying fine-scale relationships between species composition and biomass.

Keywords

Association Diversity Information statistics NDVI Non-destructive sampling 

Abbreviations

ASB

Association between species and biomass

AFB

Association between florulae and biomass

D

Level of detailedness of transformed NDVI data

DS

Difference in species richness

FD

Florula diversity

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Notes

Acknowledgements

We are grateful to Sándor Bartha, Ferkó Csillag, Geoffrey M. Henebry, and Beáta Oborny for their contribution in elaborating the novel methodology applied, and for comments on the draft. We thank György Kröel-Dulay, Gábor Ónodi and János Garadnai for their assistance in field work. This study was supported by the Hungarian Scientific Research Fund (OTKA T032319).

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© Akadémiai Kiadó, Budapest 2001

This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.

Authors and Affiliations

  1. 1.Institute of Ecology and BotanyHungarian Academy of SciencesVácrátótHungary
  2. 2.Department of Plant Taxonomy and EcologyL. Eötvös UniversityBudapestHungary

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