One Ecosystem :
Research Article
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Corresponding author: Ivo Ihtimanski (ivo.ihtimanski@gmail.com), Stoyan Nedkov (snedkov@abv.bg)
Academic editor: Joerg Priess
Received: 22 May 2020 | Accepted: 10 Sep 2020 | Published: 29 Sep 2020
© 2020 Ivo Ihtimanski, Stoyan Nedkov, Lidiya Semerdzhieva
This is an open access article distributed under the terms of the Creative Commons Attribution License (CC BY 4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Citation:
Ihtimanski I, Nedkov S, Semerdzhieva L (2020) Mapping the natural heritage as a source of recreation services at national scale in Bulgaria. One Ecosystem 5: e54621. https://doi.org/10.3897/oneeco.5.e54621
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Natural heritage includes natural features or natural areas of outstanding universal value. At a national level, this value refers to the importance of ecosystems which can be considered as the spatial units representing the natural heritage of the particular area in terms of their values to people. Nature-based outdoor recreation represents an important service that interests millions of people and contributes to connecting them to nature, but it may also cause negative impacts in the form of pollution, erosion and habitats loss. We apply the ESTIMAP recreation model which provides a framework for a spatially-explicit assessment of local outdoor recreation and use it to identify and assess the natural heritage as a source of recreation services at a national level in Bulgaria. At the first stage of the study, we identify the natural heritage and the data sources to represent it in a spatially-explicit way. Then, we apply the module for recreation potential to assess the potential of the natural heritage to provide a recreation ecosystem service. At the third stage, the accessibility of the natural heritage is assessed in order to specify how the potential identified at the previous step can be really used. Finally, the recreation potential and accessibility are integrated into the recreation opportunity spectrum in order to develop the maps representing the ecosystem service supply provided by the natural heritage. The results are presented in form of a recreation potential map that reveals the capacity of natural heritage to provide the recreation potential, map of the accessibility of the natural heritage and map of the recreation opportunity spectrum representing the combination between the first two maps. The maps will be used for the development of an innovative geospatial platform designed to facilitate the access of the Bulgarian natural heritage to the European common knowledge and innovation markets. The results on the accessibility and recreation opportunity spectrum contribute to the development of the model in areas which were not covered by previous applications at the EU scale.
Ecosystem services, ESTIMAP, GIS, recreation potential, recreation opportunity spectrum, hemeroby index, tourism
According to the World Heritage Convention, Natural Heritage (NH) includes natural features consisting of physical formations, geological features and physiographical formations, natural sites or precisely delineated natural areas of outstanding universal value from the point of view of science, conservation or natural beauty (
Outdoor recreation represents an important service that interests millions of people and contributes to connecting them to nature. It includes both local and long term recreation. The former is not considered as tourism because there is no overnight stay, while the latter can be represented as touristic outdoor recreation. These activities have an important role in human well-being and health since they provide physical, aesthetic and cultural benefits and offer an opportunity to experience directly a relationship with nature (
The sustainable use of the NH for recreational purposes in Bulgaria is the main problem addressed by this study. It is a part of a broad research project (Center for Excellence “Heritage BG"*
The ESTIMAP recreation model is based on “Advanced multiple-layer Look-up Tables” which assigns ES scores to land features according to their capacity to provide the service (
In this respect, the main objective of this study is to utilise the ESTIMAP recreation model to identify and assess the NH as a source of recreation services at a national level in Bulgaria. In this paper we aim;
We utilised the ESTIMAP recreation model as a methodological basis of our study (Fig.
The approach, developed in this work, is applied at the national level in Bulgaria, therefore the mapping was implemented for the whole area of the country. Due to the diverse climatic, geological, topographic and hydrological conditions, Bulgaria is amongst the richest countries in Europe in terms of biodiversity and geodiversity. The country accounts for about 2.5% of the total EU area, but there are 26% of all European species, 70% of the protected bird species and 40% of the conservation habitats*
Bulgaria has a total of 10 cultural and natural sites of exceptional value for humanity in the World Heritage List (MOEW 2019*
An important aspect of NH is the naturalness of the landscapes in the country. The main source of spatial data about the landscapes is the CORINE Land Cover (CLC). It has a 3-levels hierarchical classification system with five classes at the first level and 44 classes at the third level. At the first level, Bulgaria has all five classes distributed as follows: agriculture areas (51.66% of the country territory); artificial surfaces (4.79%); forest and semi-natural areas (42.55%); water bodies and wetlands (0.99%) (Fig.
The ESTIMAP recreation model needs geospatial data, which are used in various GIS and tabular operations for land features identification. Different ES scores need to be assigned to the land features according to their capacity to provide the service. The ES scores given to each land feature are based on expert assessment or literature review (
Data Type | Dataset Name | Source |
Land cover |
CLC 2012 (vector) - version 18 Sep 2016 |
https://sdi.eea.europa.eu/catalogue/srv/eng/ |
Nationally designated areas (CDDA) |
CDDA (ArcGIS geodatabase file) |
https://www.eea.europa.eu/data-and-maps/data/nationally-designated-areas-national-cdda-14 |
Bathing water quality (European Environment Agency - EEA) |
Bathing Water Directive - Status 1990 - 2018 |
https://www.eea.europa.eu/data-and-maps/data/bathing-water-directive-status-of-bathing-water-11 |
CLC 2000 coastline |
CLC 2000 coastline |
https://www.eea.europa.eu/data-and-maps/data/corine-land-cover-2000-coastline |
The elevation horizontals more than 1000 m above sea level |
O_BgContour |
The study on integrated water management in the Republic of Bulgaria – created for the Ministry of Environment and Water by Japan International Cooperation Agency (JICA) |
Urban areas in the Republic of Bulgaria |
A_BgSettle_Poly |
The study on integrated water management in the Republic of Bulgaria – created for the Ministry of Environment and Water by Japan International Cooperation Agency (JICA) |
The road network in the Republic of Bulgaria |
T_BgRoad |
The study on integrated water management in the Republic of Bulgaria – created for the Ministry of Environment and Water by Japan International Cooperation Agency (JICA) |
The natural elements that can be recognised as a heritage for the purposes of the study are selected according to the national classifier of the sites of importance for NH. This classifier has been developed within the framework of the project “Heritage BG”*
These categories have been combined with the ESTIMAP criteria for RP to define the following four main components for identification of NH as a source of recreation ES:
The DN can be described as the difference between the current and the potential natural state of a particular area to define to what extent it was transformed by human impact. In our case, the DN is a measure to identify the areas with preserved NH from those which are transformed into systems dominated by anthropogenic elements. The latter could also have some components of the NH, but they are not recognisable when the mapping is at a national level. The most appropriate source of spatial data is CLC which is available for the whole country and its classes can be easily related to specific categories representing the DN.
The presence of NP is used as additional information to emphasise the importance of the natural areas which have already been recognised as areas with special value. This value has been legally anchored by the specific restrictive regime of each protected area. Thus, the protection status of the different protected areas can be used to categorise them according to their natural value and, respectively, to identify their contribution to the NH. We use the DN and NP as the basis to distinguish the areas with preserved NH from those without.
Water is one of the main components of NH, especially in relation to recreation (
The topography is also an important component of recreation as the areas with mountainous relief are usually more attractive for people (
The assessment of the RP of the NH is based on the four main components described in the previous subchapter which have been used to derive indicators representing the capacity of the areas to provide outdoor recreation (Fig.
Degree of naturalness component:
For assessing the DN, we use CLC as a geospatial input. We use the hemeroby index as an indicator for the naturalness of the land cover classes. Firstly, the original scale of the hemeroby index is inverted in order to fit the scale used in our approach. Thus, the classes with higher anthropogenic impact receive a lower score, while those with better preserved natural elements receive a higher score. For instance, the continuous urban fabric (class 111) has the highest score (7) according to the original scheme and it is converted into the lowest (0). The scores of the CLC categories and their correspondence to the hemeroby indices are given in Table
CLC category | CLC code | CLC class | Hemeroby description | Hemeroby Index | DN Score |
Artificial surfaces | 111 | Continuous urban fabric | Metahemerobic - Excessively strong human impacts | 7 | 0 |
Artificial surfaces | 112 | Discontinuous urban fabric | Polyhemerobic - Very strong human impacts | 6 | 1 |
Artificial surfaces | 121 | Industrial or commercial units | Metahemerobic - Excessively strong human impacts | 7 | 0 |
Artificial surfaces | 122 | Road and rail networks and associated land | Metahemerobic - Excessively strong human impacts | 7 | 0 |
Artificial surfaces | 123 | Port areas | Metahemerobic - Excessively strong human impacts | 7 | 0 |
Artificial surfaces | 124 | Airports | Metahemerobic - Excessively strong human impacts | 7 | 0 |
Artificial surfaces | 131 | Mineral extraction sites | Polyhemerobic - Very strong human impacts | 6 | 1 |
Artificial surfaces | 132 | Dump sites | Polyhemerobic - Very strong human impacts | 6 | 1 |
Artificial surfaces | 133 | Construction sites | Polyhemerobic - Very strong human impacts | 6 | 1 |
Artificial surfaces | 141 | Green urban areas | Euhemerobic - Moderate - strong human impacts | 4 | 3 |
Artificial surfaces | 142 | Sport and leisure facilities | Euhemerobic - Strong human impacts | 5 | 2 |
Agricultural areas | 211 | Non-irrigated arable land | Euhemerobic - Strong human impacts | 5 | 2 |
Agricultural areas | 212 | Permanently irrigated land | Euhemerobic - Strong human impacts | 5 | 2 |
Agricultural areas | 213 | Rice fields | Euhemerobic - Strong human impacts | 5 | 2 |
Agricultural areas | 221 | Vineyards | Euhemerobic - Strong human impacts | 5 | 2 |
Agricultural areas | 222 | Fruit trees and berry plantations | Euhemerobic - Strong human impacts | 5 | 2 |
Agricultural areas | 231 | Pastures | Euhemerobic - Moderate - strong human impacts | 4 | 3 |
Agricultural areas | 242 | Complex cultivation patterns | Euhemerobic - Strong human impacts | 5 | 2 |
Agricultural areas | 243 | Land principally occupied by agriculture, with significant areas of natural vegetation | Euhemerobic - Moderate - strong human impacts | 4 | 3 |
Forest and semi-natural areas | 311 | Broad-leaved forest | Oligohemerobic - Weak human impacts | 2 | 5 |
Forest and semi-natural areas | 312 | Coniferous forest | Mesohemorobic - Moderate human impacts | 3 | 4 |
Forest and semi-natural areas | 313 | Mixed forest | Mesohemorobic - Moderate human impacts | 3 | 4 |
Forest and semi-natural areas | 321 | Natural grasslands | Mesohemorobic - Moderate human impacts | 3 | 4 |
Forest and semi-natural areas | 324 | Transitional woodland-shrub | Mesohemorobic - Moderate human impacts | 3 | 4 |
Forest and semi-natural areas | 333 | Sparsely vegetated areas | Mesohemorobic - Moderate human impacts | 3 | 4 |
Wetlands | 411 | Inland marshes | Oligohemerobic - Weak human impacts | 2 | 5 |
Wetlands | 412 | Peat bogs | Oligohemerobic - Weak human impacts | 2 | 5 |
Water bodies | 511 | Watercourses | Euhemerobic - Moderate - strong human impacts | 4 | 3 |
Water bodies | 512 | Water bodies | Euhemerobic - Moderate - strong human impacts | 4 | 3 |
Natural protection component:
For this component, we use “Nationally designated areas (CDDA)” as a geospatial input. The scores, based of the assessment presented in
IUCN Category |
Designated area |
ESTIMAP Score |
NP score |
IV |
Managed Reserve |
0.8 |
1 |
II |
National Park |
0.8 |
1 |
III |
Natural Monument |
1 |
2 |
V |
Nature Park |
0.8 |
1 |
VI |
Protected Site |
0.8 |
1 |
Not Reported |
Ramsar Site, Wetland of International Importance |
0.8 |
1 |
Not Reported |
Site of Community Importance (Habitats Directive) |
0.8 |
1 |
Not Reported |
Special Protection Area (Birds Directive) |
0.8 |
1 |
Not Reported |
State Game Husbandries |
0.8 |
1 |
Ia |
Strict Nature Reserve |
0 |
0 |
Not Applicable |
UNESCO-MAB Biosphere Reserve |
0.8 |
1 |
Not Applicable |
World Heritage Site (natural or mixed) |
0.8 |
1 |
Water component:
As described above, the water component is assessed using two parameters, coastal areas and bathing water. In order to generate a geospatial input for the coastal areas, we use a CLC layer with the coastline of Bulgaria. The coastline is transformed from line to polygon (1 km buffer). For the second parameter, we use the bathing water quality status data provided by EEA in .xlsx format for the year 2018. The initial data are georeferenced and a point layer is created. Then the point layer is transformed into polygons (400 m buffer) and the scores are assigned according to Table
EEA scores | WC score |
Excellent - Good | 2 |
Poor - Not classified | 0 |
Sufficient | 1 |
Topography:
The layers representing the components described above (DN, NP and WC) are united in one feature class. The scores for each component are summed for any CLC class, designated area or water body. For the areas above 1000 m, the summed score is increased by 1 in order to reflect the additional component topography. Then the final score is classified according to the scheme given in Table
At the third step of the analysis, the accessibility of the NH is addressed in order to assess how the recreation can be delivered to people. The accessibility is based on the distance of the NH to settlements and roads. The Accessibility map is generated from vector feature classes - Urban areas and Road network in the Republic of Bulgaria. The Euclidean distance is computed for the two layers. The rasters with computed distance are combined using the ArcGIS raster calculator to create the Accessibility layer. The Accessibility layer is converted to a vector map and, in the cases where a polygon falls in two zones, the higher one is taken. The polygons are assigned a score according to Table
The ROS represents how people can benefit from the opportunities provided by nature for recreational activities if they are able to reach them (
ROS | Accessibility | RP |
No potential | Near | No potential |
Low potential - not easily accessible | Far | Low potential |
Low potential – accessible | Proximal | Low potential |
Low potential - easily accessible | Near | Low potential |
Medium potential - not easily accessible | Far | Medium potential |
Medium potential – accessible | Proximal | Medium potential |
Medium potential - easily accessible | Near | Medium potential |
High potential - not easily accessible | Far | High potential |
High potential - accessible | Proximal | High potential |
High potential - easily accessible | Near | High potential |
Very high potential – accessible | Proximal | Very high potential |
Very high potential - easily accessible | Near | Very high potential |
The RP map (Fig.
Three percent of the country’s territory is covered by areas with no potential for recreation. Most of these areas are artificial surfaces excluding green urban areas and sport and leisure facilities, which have higher potential. The areas identified with a score of 1 - Low potential are mostly agricultural areas and some forest and semi-natural areas covering around 52% from the country.
The areas with high and very high RP are less than one percent, they are mostly forest and semi-natural areas, agricultural areas and wetlands. Some sports and leisure facilities also have high and very high RP. Most of the areas with the highest RP are located on the Black Sea coast and in the high mountain areas, but they are too small and could not be easily recognised on the national scale map (Fig.
The map of the accessibility of the NH (Fig.
The map of the ROS in Bulgaria (Fig.
The distribution of the different ROS combination is given in Table
ROS |
Area in hectares |
% |
Very high potential - easily accessible |
465.8 |
0.003% |
Very high potential– accessible |
93.1 |
0.001% |
High potential - easily accessible |
3702.6 |
0.026% |
High potential– accessible |
1287.7 |
0.009% |
High potential - not easily accessible |
70.0 |
0.000% |
Medium potential - easily accessible |
4174681.3 |
29.466% |
Medium potential– accessible |
1833758.6 |
12.943% |
Medium potential - not easily accessible |
380738.8 |
2.687% |
Low potential - easily accessible |
6738163.5 |
47.559% |
Low potential– accessible |
556338.1 |
3.927% |
Low potential - not easily accessible |
92561.2 |
0.653% |
No potential |
386089.6 |
2.725% |
All |
14167950.9 |
100.000% |
As is mentioned above, a limited area (less than 1%) is located in zones with high and very high potential. The places where these two zones match with easy accessibility are located predominantly at the Black Sea coast and few of them in the high mountains (Fig.
In this study, we apply the ESTIMAP recreation model to identify, assess and map the RP of the NH at the national level in Bulgaria. The original model configuration has been adapted for the needs of the study by increasing the spatial resolution using local vector data instead of raster data and adding one new component for the assessment of the RP. This component is based on the assumption that mountain regions have a special attraction for recreation and generate higher values per visit. Such an assumption has been also discussed by
The ESTIMAP recreation model was applied for the whole EU, but the results for Bulgaria and Romania were included only in the map of the RP (
The approach of the ESTIMAP model is intuitive and relatively easy for application at various scales. Most of the required data are available for free which facilitates its applicability. The approach is flexible to the addition of other indicators and data that can improve the quality of the results. On the other hand, data manipulation is sometimes redundant and time-consuming. The scores of the RP are somehow subjective as they are based on expert assessment, therefore further improvements of the approach could be in the form of incorporation of more empirical data for this process. Some CLC classes (322 - Moors and heathland; 323 - Sclerophyllous vegetation; 331 - Beaches, dunes, sands; 332 - Bare rocks; 334 - Burnt areas; 421 - Salt marshes; 422 - Salines; 521 - Coastal lagoons; 523 - Sea and ocean) are not included in the hemeroby index assessment given by
One limitation of the approach is that there are some other factors for the RP of the NH, such as climate condition, terrain morphology, fragmentation of landscapes etc. which are not incorporated in the current version of the model. There are also NH sites in areas not identified as such, for instance in urban areas. These limitations are admissible for studies at a national level due to the lack of appropriate data or the degree of their importance, but for future studies at a local level, more comprehensive adaptation of the ESTIMAP model is necessary.
The results of this study will be used as a basis to develop the ES component of a geospatial platform for access to the Bulgarian NH. Such a platform can be used for geospatial analysis of multiple threats to and from tourism (
With the adaptation of the ESTIMAP model, we have managed to identify the spatial extent of the NH in Bulgaria at a national scale, to assess its RP and accessibility and derive ROS. These results could be considered as a basis for assessment of the capacity of Bulgarian NH to provide recreational ES. The maps of the RP, the accessibility and the ROS will be used for the development of an innovative geospatial platform designed to facilitate the access of the Bulgarian NH to the European common knowledge and innovation markets. The outputs of the platform will be used in the spatial planning and implementation of the recreational industries and will support the capitalisation of the future products in relation to various business entities. The results of the outdoor recreation could be used in analyses of the RP and its accessibility for the needs of the district tourism management plans. The ROS results will be integrated into the geospatial platform in order to develop a tool for place-based analyses which can be used by the tourism companies in their investment activities.
More indicators, such as climate conditions, landscape pattern and topography, as well as more detailed and precise data about the current indicators, should be added for further development of the model in Bulgaria in order to achieve more reliable and representative results. An indicator of the riparian vegetation should be added to reveal this important recreational aspect. The accessibility part should be improved with actual data on the population density because the available data are from 2011. The road network data should be developed with railways, small roads and hiking trails. The implementation of the model at a local level assumes upgrading the current data with more detailed NH objects, such as the open geospatial database OpenStreetMap etc. (as, for instance,
The study is supported by the project BG05M2OP001-1.001-0001 "Building and Development of Center for Excellence "HeritageBG", funded by the OP Science and Education for Innovative Development 2014-2020, co-financed by the European Regional Development Fund“. It is also part of a PhD work supported by the National Institute of Geophysics Geodesy and Geography at the Bulgarian Academy of Sciences.