198
Views
6
CrossRef citations to date
0
Altmetric
Original Articles

Applicability of full inversion tillage to semi-natural grassland restoration on ex-arable land

, , &
Pages 785-795 | Received 05 Apr 2014, Accepted 28 Aug 2014, Published online: 23 Sep 2014
 

Abstract

The application of full inversion tillage (FIT) for the creation of semi-natural grasslands on ex-arable land raises the question of its influence on the availability of soil mineral nutrients as increased soil fertility may cause competitive exclusion of the target plant species. This work is an attempt to answer how FIT influences the availability of N, P, K and Mg and associated soil properties and accordingly how to use this method so that elevated nutrients availability during the establishment of semi-natural grassland species could be avoided. An experiment was conducted in 2-ha area of abandoned fields in east Poland, on Rendzic, Cambic Leptosol and Mollic Gleysol. The area was divided into 8-m-wide strips, every second of which was subjected to FIT; 19 pairs of permanent plots were regularly allocated across the area, each pair containing a plot located on a cultivated strip and a plot on the neighbouring control strip. The comparison of soil properties within the pairs resulted in no significant differences, except for a lower K status in the FIT plots. Presumably FIT did not change the soil conditions in a way which could affect the intensity of the inter-specific competition in a newly created plant community.

Acknowledgements

We thank Dr Liz Price for the detailed review of this manuscript and very helpful comments on it.

Log in via your institution

Log in to Taylor & Francis Online

PDF download + Online access
  • 48 hours access to article PDF & online version
  • Article PDF can be downloaded
  • Article PDF can be printed
USD 61.00 Add to cart
* Local tax will be added as applicable

Related Research

People also read lists articles that other readers of this article have read.

Recommended articles lists articles that we recommend and is powered by our AI driven recommendation engine.

Cited by lists all citing articles based on Crossref citations.
Articles with the Crossref icon will open in a new tab.