A1 Refereed original research article in a scientific journal

Assessing Restoration Potential of Semi-natural Grasslands by Landscape Change Trajectories




AuthorsTimo P. Pitkänen, Maija Mussaari, Niina Käyhkö

PublisherSpringer

Publication year2014

JournalEnvironmental Management

Volume53

Issue4

First page 739

Last page756

Number of pages18

ISSN0364-152X

eISSN1432-1009

DOIhttps://doi.org/10.1007/s00267-014-0242-x

Web address http://link.springer.com/article/10.1007%2Fs00267-014-0242-x


Abstract

Species-rich semi-natural grasslands have rapidly declined and become fragmented in Northern Europe due to ceased traditional agricultural practices and animal husbandry. Restoration actions have been introduced in many places to improve the habitat conditions and increase the area to prevent any further losses of their ecological values. However, given the limited resources and long time span needed for successful restoration, it is essential to target activities on sites having a suitable initial state and where the effects of restoration are most beneficial for the habitat network. In this paper we present a conceptual framework for evaluating the restoration potential of partially overgrown and selectively managed semi-natural grasslands in a moderately transformed agricultural environment in south-western Finland. On the basis of the spatio-temporal landscape trajectory analysis, we construct potential restoration scenarios based on expected semi-natural grassland characteristics that are derived from land productivity, detected grassland continuum, and date of overgrowth. These scenarios are evaluated using landscape metrics, their feasibility is discussed and the effects of potential restoration are compared to the present extent of open semi-natural grasslands. Our results show that landscape trajectory analysis and scenario construction can be valuable tools for the restoration planning of semi-natural grasslands with limited resources. The approach should therefore be considered as an essential tool to find the most optimal restoration sites and to pre-evaluate the effects.



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