Abstract

The aim of the EU Biodiversity Strategy to 2020 isto maintain and enhance ecosystem services (ES) in Europe and requires all Member States to map and assess the state of ecosystems and their services in the respective national territories. The EU-funded project ESMERALDA analyses ES mapping and assessment methods and approaches in their biophysical, social and economical perspectives, as well as their application in different case studies. The project also aims at the development of an integrated and consistent assessment framework. In Bulgaria, methodological guides for evaluation and mapping of the services provided by the nine main types of ecosystems have been prepared together with the respective proposals for their implementation in the national assessment. The Bulgarian research team analyses and tests various aspects of ecosystem services mapping and assessment, such as alternative economic assessments, multi-criteria analyses and biophysical assessment approaches, mapping challenges and local population surveys. In this paper paper, we review the ES activities in Bulgaria and present selected mapping and assessment methods tested in the Central Balkan case study area. It provides relevant examples for the implementation of integrated mapping and assessment of ecosystem services at local and regional level, where different mapping approaches and techniques are embedded within diverse policy contexts. The main goal of the study is to investigate how the assessment results can support the integration of the ecological functions of the Central Balkan National Park with the economic opportunities that it creates for the local and regional communities. A tiered approach has been used to organise the mapping and assessment exercises in the study area, in order to meet the needs for integrated ecosystem assessment and overcome the limitations of data availability. At tier 1, the study performs identification and initial ES mapping of the whole area. At tier 2, it applies economic valuation for the Municipality of Karlovo by using statistical data and the contingent valuation method. At tier 3, the investigation applies modelling methods to assess carbon storage and flood regulation on a larger scale. The results are presented in the form of maps at all levels, which use a uniform 0 to 5 assessment scale. The integrated approach presented here ensures a clear communication of the end results to the respective decision-makers.

Highlights

  • The natural world, its biodiversity and its constituent ecosystems are critically important to human well-being and economic prosperity, but are consistently undervalued in conventional economic analyses and decision-making (UK and NEA 2011)

  • The relevant ecosystem services for the case study area were selected using the CICES classification by the authors of this study and they were placed at the x-axis of the matrix

  • This paper follows the general structure of the framework for integrated mapping and assessment of ecosystem services provided by Burkhard et al 2018 in the Central Balkan case study area

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Summary

Introduction

The natural world, its biodiversity and its constituent ecosystems are critically important to human well-being and economic prosperity, but are consistently undervalued in conventional economic analyses and decision-making (UK and NEA 2011). The EU Biodiversity Strategy to 2020 aims, under its Target 2, to maintain and enhance ecosystem services (ES) in Europe. The EU-funded project, ESMERALDA (Enhancing ecosystem sERvices mApping for policy and Decision mAking), aims to deliver “flexible methodology that can simultaneously provide innovative building blocks for panEuropean, national and regional ES mapping and assessment” (ESMERALDA 2015). It analyses ES mapping and assessment methods and approaches in their biophysical, social and economical perspectives, as well as their application through testing in different case studies (Burkhard 2018). The tiered approach is promoted as an instrument to structure a variety of methods by applying them to different complexity levels

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