Environmental Management

, Volume 59, Issue 3, pp 505–521

Identification of the Criteria for Decision Making of Cut-Away Peatland Reuse


DOI: 10.1007/s00267-016-0797-9

Cite this article as:
Padur, K., Ilomets, M. & Põder, T. Environmental Management (2017) 59: 505. doi:10.1007/s00267-016-0797-9


The total area of abandoned milled peatlands which need to be rehabilitated for sustainable land-use is nearly 10,000 ha in Estonia. According to the agreement between Estonia and the European Union, Estonia has to create suitable conditions for restoration of 2000 ha of abandoned cut-away peatlands by 2023. The decisions on rehabilitation of abandoned milled peatlands have so far relied on a limited knowledgebase with unestablished methodologies, thus the decision making process needs a significant improvement. This study aims to improve the methodology by identifying the criteria for optimal decision making to ensure sustainable land use planning after peat extraction. Therefore relevant environmental, social and economic restrictive and weighted comparison criteria, which assess reuse alternatives suitability for achieving the goal, is developed in cooperation with stakeholders. Restrictive criteria are arranged into a decision tree to help to determine the implementable reuse alternatives in various situations. Weighted comparison criteria are developed in cooperation with stakeholders to rank the reuse alternatives. The comparison criteria are organised hierarchically into a value tree. In the situation, where the selection of a suitable rehabilitation alternative for a specific milled peatland is going to be made, the weighted comparison criteria values need to be identified and the presented approach supports the optimal and transparent decision making. In addition to Estonian context the general results of the study could also be applied to a cut-away peatlands in other regions with need-based site-dependent modifications of criteria values and weights.


Peatland rehabilitation Milled peatland Decision making Stakeholders Decision tree Criteria system 

Copyright information

© Springer Science+Business Media New York 2016

Authors and Affiliations

  1. 1.Tallinn UniversityTallinnEstonia

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