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Article

Landscape Structure and Fragmentation: Key Factors in the Characterisation of Urban and Peri-Urban Forests in Slovenia

by
David Hladnik
and
Mojca Nastran
*
Biotechnical Faculty, Department for Forestry and Renewable Forest Resources, University of Ljubljana, Večna pot 83, 1000 Ljubljana, Slovenia
*
Author to whom correspondence should be addressed.
Land 2023, 12(11), 1968; https://doi.org/10.3390/land12111968
Submission received: 22 August 2023 / Revised: 20 October 2023 / Accepted: 21 October 2023 / Published: 25 October 2023
(This article belongs to the Section Landscape Ecology)
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Abstract

:
Urban and peri-urban forests are strongly influenced by urbanisation and infrastructure-driven development. The main objective of the study is to evaluate and assess key factors characterising of urban and peri-urban forests in Slovenian regions with large differences in landscape fragmentation, from the Pannonian Plain to the Alps and the Mediterranean Sea. To assess landscape fragmentation and potential urban and peri-urban forests (UPFs), we used a spatial model of landscape structure and spatial characteristics of forests’ fragmentation and connectivity. The basis for estimating landscape structure and spatial characteristics of UPFs was tested for the 69 settlements with city status and for 150 smaller, rural settlements, which are the centres of individual municipalities. Of the 219 Slovenian settlements analysed, forest core areas within walking distance were estimated for 98% of the settlements. The proportion of the walking distance area with forest cover and 100 m or more from the forest edge is no more than one tenth of this area for 45% of Slovenian towns and for 42% of smaller settlements. By assessing the gradients of landscape ecological variables and accessibility of UPFs, it is possible to compare UPFs in different regions and take them into account when preparing guidelines for spatial planning based on landscape structure principles at the local level. Large differences in the landscape and UPF fragmentation within cities and settlements highlight the importance of spatial planning that adapts to the individuality of the landscape and each UPF.

1. Introduction

Rapid urbanisation and growing urban populations underscore the importance of green spaces for human well-being [1,2]. Urban forestry and landscape ecology play a vital role in preserving nearby natural ecosystems and ensuring their accessibility to urban dwellers [3,4]. Analysing urban and peri-urban landscape structures aids in optimising the benefits and minimising the harmful consequences of human interventions [5].
To support UPFs’ planning and management, understanding their characteristics and influences on landscape structure is essential. Urbanisation and infrastructure development significantly affect UPFs by reducing their area and causing fragmentation, necessitating clear analysis for successful protection and management.
Fragmentation of the landscape is the process and result of the conversion of large areas of homogeneous landscape units into lesser habitats. This process is most pronounced in peri-urban areas due to linear infrastructure connections. In addition to fragmentation, habitats are also more isolated because they are separated by roads or railway lines that are difficult to pass [6].
Fragmentation of natural ecosystems around urban areas strongly affects biodiversity [7]. High levels of fragmentation are found around major urban centres and major infrastructure. UPFs are highly susceptible to shrinking and fragmentation due to the rapid urbanisation of peri-urban areas [8]. The fragmentation of UPFs degrades the quality and quantity of accessible forests that serve an individual function by reducing patch size, increasing distance from the city, increasing the fragmented distribution in the landscape, and reducing the depth of the patch interior. Larger patches of forest correspond to species requiring larger areas of closed habitats. The distance between patches and the lack of corridors make it more difficult for species to move through an area and thus to maintain genetic variability [9,10]. The fragmentation of a forest reduces its climatic function. Larger, more closed forest areas have a greater impact on urban heat island mitigation [11]. Also, the recreational and gathering function of the forest depends on the fragmentation of patches, their size, and the connections between them [12]. Fragmentation of forest patches therefore has a major impact on all the factors or criteria presented above that can define UPFs.
A huge amount of research has looked at individual ES of UPFs [13], but sometimes the research is difficult to compare due to the broad and vague definition of urban forests. UPFs’ boundaries are most often presented as fact in research. Can the definition of an UPF be narrowed down at all? When it comes to more precise definitions, there is a lack of uniformity in the international definition of both forest and urban areas. Pregitzer et al. [14] highlight the looseness of definitions of UPFs versus (non-urban) forests, which varies between countries. This is usually based on land cover, the administrative unit, minimum canopy cover, fragment size, vegetation height, etc. [15]. UPFs definitions are more loose and based on national specificities (e.g., [16]). However, broad, general definitions capture well the very different, historically driven, and international perceptions of the various disciplines dealing with forests and trees in the urban environment: “Urban forests can be defined as networks or systems comprising all woodlands, groups of trees, and individual trees located in urban and peri-urban areas; they include, therefore, forests, street trees, trees in parks and gardens, and trees in derelict corners” ([7], p. 2). It is generally accepted that UPF definitions define urban forest ecosystems and not only street trees and parks [13]. The distinction between a peri-urban and urban forest complicates the tangible definition, with some referring to it as a suburban forest (e.g., [17,18]). Location-based criteria become less clear, and emphasis shifts to functions typical of urban forests.
The definition of an UPF has significantly implications for forest management, regulations, and spatial planning. It should align with protection and management objectives. The criteria for defining UPFs vary, making it challenging to create exact, reproducible definitions. The boundary between urban and other forests depends on spatial policy, planning, and communication between planners, often satisfying multiple criteria and following local, cultural, and historical specificities [13]. Studies on urban green space provision and accessibility have predominated in larger European cities but must expand to individual municipal settlements due to varying spatial processes [19,20,21,22].
Common criteria for UPF designations include proximity to urban areas, contributions to urban well-being, historical traditions, legal regulations, forest management, and fragmentation, which are all interconnected.
We usually think only of forests adjacent to or within major metropolitan areas, but some definitions of urban forests also include and emphasise forests adjacent to smaller towns and rural settlements, such as those that characterise Slovenia. For example, Miller ([23], p. 27) defines urban forests as “the sum of all woody and associated vegetation in and around dense human settlements, ranging from small communities in rural settings to metropolitan regions”, and Jorgensen [24] defines urban forestry as “not only dealing with city trees or with single tree management, but also with tree management in the entire area influenced by and utilized by the urban population”. Location can also be associated with the distance of the forest from urban areas. Research identifies distance as one of the most important factors in the amount of recreation in UPFs [19,25]. Few studies have used specific criteria, with some relying on proximity to urban areas, such as of 1 km or a 15 min walk from built-up areas [3,5,19,20].
Urban Public Forests (UPFs) emphasise ecological and social functions, with economic roles like timber production being secondary. Miller [23], in his description of urban forestry, also emphasises management to provide psychological, sociological, economic, and aesthetic benefits to society. UPFs have been used as a recreational space, a source of water resources, and a source of timber. Other functions are often attributed to UPFs, most often biotic, climatic, and aesthetic. The distribution, size, and conservation of forest patches are important in this context (e.g., [11,26]). Some cities set UPFs by regulation, which follows the above criteria in determining their extent. The regulations record the emphasised functions, the management adapted to them, and the rights and duties of forest owners. In general, cities tend to take possession of the forest as much as possible, which makes the management of UPFs with cultural function much easier.
The rich tapestry of ecological, spatial, and social factors that shape these urban and peri-urban green spaces demands innovative and rigorous research method. Landscape structure and fragmentation of a UPF can be measured through landscape metrics, but often the comparability between individual surveys depends on the spatial resolution, scale, and extent of observation [27,28,29].
In recent decades, landscape metrics, such as patch size, shape, core area metrics and connectivity indices, have been widely used to quantify the spatial structure and fragmentation of UPFs [30,31,32]. These metrics provide quantitative measures of landscape patterns and are useful for comparing different study areas. However, the choice of metrics can significantly impact the results, and the interpretation of these indices may vary based on the context. From a comprehensive set of fragmentation indicators, it is appropriate to refer to those that have been used effectively in comparison of individual regions [6] or integrated into guidelines to prevent further landscape and habitat fragmentation [10,33]. The general guidance provided should not be seen as a substitute for detailed studies of landscape structure but as a representation of a harmonised approach for decision-making in spatial planning.
To date studies assessing urban green space provision and accessibility in larger cities have understandably dominated at the European level and in individual EU countries [22,34,35,36]. As the processes of urbanisation, landscape fragmentation and land use intensification take place at different spatial scales, there is a need to assess the characteristics and importance of UPFs down to the level of individual municipal settlements. In our work, we want to show this transition of UPFs’ characteristics from the largest cities to individual settlements.

Research Objectives

In order to formulate spatial policy guidelines down at the level of the landscape structure along the smallest settlements, we need harmonised information on their characteristics. Our research has mainly focused on the analysis of the spatial characteristics of UPFs, the characteristics and quality of which are strongly influenced by fragmentation. The main objective of the research is to evaluate and assess key factors in characterising UPFs from a landscape ecology perspective, which was achieved with the following steps:
  • A baseline is established for the assessment of the fragmentation of Slovenian landscapes and potential peri-urban and urban forests, placing them in the context of the landscape structure and its fragmentation.
  • The accessibility of urban areas to the inner environment of forest patches is identified. The accessibility of forest patches is the most important criterion affecting their interaction with urban areas.
  • Based on parameters of landscape structure and its fragmentation and the accessibility of forest patches adjacent to urban areas, a gradient of variables can be estimated for peri-urban forests and forests adjacent to settlements. By assessing gradients, it is possible to compare peri-urban forests in different countries and regions and to take them into account when drawing up guidelines for spatial planning based on landscape structure principles at the local level.

2. Methods and Data

2.1. Suitability of Slovenia for the Evaluation and Assessment of Criteria for Urban and Peri-Urban Forests

Slovenia was chosen for the analysis because it comprises regions with large differences in landscape fragmentation, from the Pannonian Plain to the Alps and the Mediterranean Sea. Two regions in the east of the country belong to the group of the most highly fragmented European regions, and three regions in the west belong to a group comparable to the European regions with lower fragmentation levels [6]. The areas at higher altitudes and their surroundings have lower levels of fragmentation.
The structure of the Slovenian cultural landscape is threatened, on the one hand, by the overgrowth of agricultural land in the hills and, on the other hand, by the intensification of agricultural activity and the spread of urban areas in the lowlands. Both processes are taking place at different scales: from (i) the largest Slovenian cities, comparable in size to larger cities in other countries, to (ii) individual settlements, which do not even have the status of a city in terms of their size but are dwellings of the inhabitants of local communities with the autonomous right and obligation to decide on spatial planning at the local level.

2.2. Site Selection and Data

The assessment of potential UPFs was carried out in a hierarchical way, considering the scale of Slovenian towns and cities. Slovenia is divided into 212 municipalities, where only 69 have the status of a city. Only the largest towns and villages with at least 5000 inhabitants are comparable to the categorisation of cities proposed for international comparisons to define urban and rural areas [37]. Unlike other European countries with rapid urbanisation, Slovenia is characterised by suburbanisation and a relatively low share of urban population, not exceeding 50%.
Slovenia has 2.1 million inhabitants living in 5978 settlements [38]. A total of 737,000 inhabitants live in the 30 largest Slovenian cities, which corresponds to 36% of the total population of the country (Ministry of Environment and Space of the Republic of Slovenia, 2016). Only six Slovenian cities have more than 25,000 inhabitants (Figure 1). We used data from Slovenian cities and municipalities [38] to select urban settlement centres. All NUTS-3 statistical units are included in the analysis of settlements and all municipalities in the country are represented (Figure 1).
As 44% of the Slovenian population live in settlements with less than 1000 inhabitants [38], all municipal centres were also included in the analysis of UPFs. In total, we analysed the spatial characteristics of forests and landscape structure in 69 Slovenian towns and cities and in 150 settlements that are the centres of individual Slovenian municipalities. This analysis provided scores on various spatial scales in order to assess the importance of UPFs and their accessibility to inhabitants. The different assessment criteria are already illustrated by the classification of Slovenian municipalities according to size classes, area, and population (Figure 2).
For comparability with other countries, the urban area boundaries were taken from the CORINE LC—CLC map [39], but 48 municipal centres (32%) were not shown on this map, although the mapping area threshold was set at 25 ha. Due to a CLC coarse mapping unit, smaller settlements were delineated based on built-up land data from an agricultural land use map [40].
Since spatial planning in the smallest administrative units has a key impact on the quality of the living environment of the inhabitants, the assessment was carried out for all Slovenian municipal centres. Small municipalities dominate in terms of number, with four municipalities comprising only one settlement each [41].

2.3. Identification of UPFs through Fragmentation Analysis

We use the term ‘landscape’ in a broad definition according to Forman (1995), who conceives a landscape as a mosaic in which a group of ecosystems appears in similar form within an area. Landscape features can also be represented categorically, as in the classic patch-mosaic model of landscape structure. As he asserts, a landscape is often characterised by its spatial arrangement, composition and configuration, which play an important role in determining ecological functions, biodiversity and the overall resilience and sustainability of the system.
We combined data on road and rail networks [42] with data on urban land use [39,40] and developed a baseline for assessing the fragmentation of Slovenian landscapes according to established methods [43], which is also presented in the report “Landscape fragmentation in Europe” [6]. We defined an impact area of up to 5 m from the centreline for national and regional roads and railways, and 10 m for motorways and expressways, which is comparable to methods for assessing landscape fragmentation [43]. We also considered local and forest roads in the spatial modelling of transport infrastructure that fragments forest land.
Landscape fragmentation was assessed based on the most commonly used indicators in landscape planning, derived from the area-weighted mean patch size (AWM) [44], which is also used at the level of European countries [6] and worldwide [30,43]:
A W M = ∑ i = 1 n a i j 2 A
where aij is the area of patch i in spatial unit j, and A is the total area of the site. According to Forman [45] and Jaeger et al. [6], the assessment of landscape fragmentation is determined by the linkage of built-up areas (cities and settlements) and linear infrastructure (roads and railroads). In our work, the concept of AWM assessment has been transferred from regional and other administrative units (Figure 3 and Figure 4) to the fragmentation of landscape units surrounding individual cities and settlements. The delineation of landscape units was the first step in the assessment of landscape fragmentation. The concept of delineating spatial units and extracting individual variables to the final analysis and clustering is explained (Figure 3).
In the next step, we assessed the forests fragmentation within the network of cities, settlements, and transport corridors. Forest fragmentation was assessed by the share of forest cover, the share of forest core areas, and the share of agricultural open space. We have selected only a limited set of indicators (Table 1) that can be directly compared at different levels of forest management and spatial planning. These indicators can determine the quality of the urban environment and could provide a basis for planning new or expanded transport corridors while maintaining the accessibility and connectivity of the UPF core areas. To assess landscape structure and fragmentation down to the level of individual settlements, we used a land use map [40] and a forest stand map [46] at a scale of 1:5000 with a mapping unit of 0.25 ha.
Based on previous surveys of Slovenian urban and peri-urban forests [5,47] we assume that most of the forests in the core areas are well preserved. The forests in these areas generally have long unchanged land use and are late successional and persistent. In our research, we defined as core areas the areas that are at least 100 or 250 m away from the edges of the forest patches. Determining the size of core areas is especially important for the protection of specific species that are characteristic of the inner-forest environment. Bentrup [33] notes that the edge effect in forest and grassland areas is reduced from 300 ft to 1300 ft. Recommendations for the minimum size of forest patches vary according to the needs of the species but certainly depend on the quality of the forest stands and the context of the landscape ecology. A spherical forest patch must be at least 20 ha in size to meet the 250 m distance from edge requirement. Environment Canada [10] estimates that the smaller patches harbour bird species that tolerate the edge zone. A distance of 100 m from the forest edge is proposed as the beginning of the core area.
The connectivity of UPF patches was assessed by the depth of the open space of agricultural land surrounding cities and settlements. To maintain the spatial scale of the observation, the depth of open agricultural land was estimated using the same distance gradients as the depth of the inner environment of forest patches.

2.4. Gradients of Landscape Ecological Variables

We used principal component analysis (PCA) here to summarise the landscape ecological parameters into new principal components representing independent gradients in the configuration for each settlement. This enabled us to identify groups of settlements that are similar and determine which variables make one group different from another.
PCA arranges settlements along continuous linear gradients of variation (i.e., principal components), thereby reducing the number of dimensions. In our study, the settlements were ordinated according to their landscape structure and fragmentation (i.e., relative abundances of forest, forest core areas, and open space and abundance of intensive agricultural lands).
For the within-area analysis, based on walking distances to settlements, we used the variables forest cover (FC), share of forest core areas that are more than 100 or 250 m from the edge of a forest patch (FCA), share of intensive agriculture open space (OSA), and share of open space areas more than 250 or 500 m from the interior habitat of forest patches (OS).
We performed the analysis in the R environment for statistical computing and graphics [48]. We judged the usefulness of the final principal components using (i) the proportion of variance that the components explain, (ii) the size of the eigenvalue to determine the number of principal components, and (iii) the scree plot ordering the eigenvalues from largest to smallest. Specifically, while testing the significance of each PC using permutation-based statistical tests, we also checked the contribution of each observed variable to each significant PC [49].
Based on these significant variables, we formed clusters of settlements using the k-means method. The optimal number of clusters was determined by the elbow method (minimising the total variation within clusters) and the gap statistics method that compares the total intracluster variation for different numbers of clusters with their expected values under null reference distribution of the data.

2.5. UPF Functions and Legal Acts

The functions of forests, determined by the Slovenia Forest Service [46] and evaluated with the degree of their influence on forest management on maps and inventories of forest functions in the regional plan, are taken into account as an expert basis for spatial arrangements of national and local importance [50]. In UPFs, ecological and social functions are emphasised over production functions [51].
The Slovenian Forest Act [50] covers UPFs with the provision on Special Purpose Forests, which emphasize protective, climatic, hygienic-health, recreational, touristic, educational, and aesthetic functions, as well as functions for the protection of cultural or natural heritage. The declaration of these forests requires the consent of the owners, who are entitled to compensation if the use of their property is restricted. The local community has the right of pre-emption to these forests.

3. Results

3.1. Size and Structure of Landscape Units

The spatial extent of the largest Slovenian cities and the size of the landscape units (AWM) surrounding them show large differences in the spatial scale of the assessment of UPFs. Only Ljubljana and Maribor comprise urban areas at a scale comparable to the size of the landscape units in which landscape structure is assessed. In Table 2, we present data and indicators for the 30 largest cities so that all Slovenian regions are represented in the overview. The AWM assessment shows that landscape fragmentation cannot be inferred solely from the size of cities and the number of inhabitants, but rather from the location of road and rail corridors linking cities and the population density or distance to the next settlement. Even within the largest cities (Figure 1: Ljubljana, Maribor, Kranj), there are patches and spatial units of landscape matrix forests with deep cores areas—between 700 and 1300 m (Table 2).
In this research, we use the terms urban and peri-urban forest together since we do not distinguish between UPFs in particular. Due to its fragmented and relatively small settlements, the transition between urban and peri-urban is less pronounced. We count as UPFs all forest patches located within a certain distance from the centres of settlements. The Slovenian legislation defining urban forests (Special Purpose Forests Act) does not (so far) distinguish between urban and peri-urban forests.
In agricultural landscapes, forests are highly fragmented. The largest patches near Brežice and Murska Sobota (Figure 5c) have inner environments with depths between 150 and 250 m. The coastal town of Izola, which developed from a settlement on the original island, is also cut off by a major expressway, so the town is surrounded by landscape patches with an AWM of less than 1 km2, and we estimated the maximum depth of forest patches at 133 m. Next to the three cities with the most heavily fragmented forests, we estimated a forest cover of less than 15%. The importance of these UPFs is reflected in their multiple functions, which have been identified in the forest management plans of the Slovenia Forest Service and comprise over 90% of the total forest patch area. However, it cannot be directly inferred from these functions whether they have been identified in relation to the importance of forests adjacent to urban areas. At most, potential UPFs can be inferred for forests with climate, hygienic-health, aesthetic, and recreational functions.
While the indicators in Table 2 suggest differences in landscape structure in urban areas between regions, there are still large differences in the size of AWM, landscape structure, and fragmentation of potential UPFs within each region.
These differences were also assessed based on the distance from cities to forest patches that are expected to have a developed interior forest environment. We illustrated differences in the scale of cities by the depth of a UPF interior forest. In Zagorje (Table 2, code 5.1), the minimum depth of urban interior area was estimated at 285 m, while in Ljubljana, the largest city, it was estimated at 1300 m (Table 2: code 8.4, Figure 6).
Within each region, we estimated large differences in the size of the AWM landscape units within each city. For example, the differences between the smallest and the largest AWM in the Podravska region (code 2) are 5-fold and in the regions of southeast Slovenia (7) and central Slovenia (8) even 20-fold. The depth of the inner environments of forest patches, which is one of the indicators of UPF preservation, also varies considerably between settlements (Table 2).
For one-third of the largest Slovenian cities, we have also assessed the area of the landscape units as consisting of compacted forest patches with an interior depth of more than 800 m (Table 2), which is comparable to a circular patch with an area of 200 ha. Among the largest Slovenian cities, 16 had an interior depth of more than 560 m, which is comparable to the area of a 100 ha patch (Table 2).

3.2. Accessibility of UPFs

Most Slovenian cities have good access to forest patches, as the average distances from cities to these patches are less than 1 km, and even for the capital Ljubljana, the average distance is only 1150 m (Figure 6a). Cities with greater distances to forest patches include the coastal cities of Piran, Izola, and Koper, and cities in agricultural landscapes (Brežice, Murska Sobota, Lendava, Žalec).
The differences in the spatial structure of UPFs are more pronounced in areas that are within a walking distance of 1 km from cities. In the two coastal towns and in the town of Žalec in an agricultural landscape, we could not identify any forest patches with core areas above 100 m. In the capital city of Ljubljana, core areas accounted for 45% of the total forest patch area (Figure 6b), and forest patches with core areas above 250 m are also preserved, accounting for 17% of the forest area within walking distance. In 58 cities (84%), cores of the inner forest environment, 250 m away from the forest edges, were also assessed. In 11 other Slovenian cities, more than one fifth of the forest area was estimated to have such large core areas.
Figure 6b and Figure 7 show that the conservation of UPFs could also be based on general recommendations on the fragmentation of forest patches in the landscape. Among the 69 Slovenian cities, only nine cities were estimated to have a core area forest cover of less than 10% within walking distance. In the patches next to the cities, the areas of interior forest further than 100 m from the forest edge are still preserved and might represent important corridors and stepping stones of natural vegetation. The importance of these patches can be inferred from the estimated amount of the open agricultural and other non-forested land surrounding the cities.
In addition to Ljubljana and Maribor, we estimated higher proportions of open space (over 500 m depth) formed by agricultural land in 15 other Slovenian cities (Figure 7). The variability in the area proportions of open space of agricultural land is higher than that in the area proportions of forest patches with interior forest, but based on these indicators alone, it is not possible to draw conclusions about the influence of city size on landscape structure. In 45% of Slovenian cities and in 42% of smaller settlements, the proportion of area with forest cover 100 m or more from the forest edge is no more than one tenth of this area.

3.3. Assessment of UPF Gradients

Using the set of indicators presented so far, we assessed the landscape structure and spatial characteristics of forests within walking distance for another 150 settlements, which are the centres of individual municipalities in Slovenia. PCA provides a starting point for classifying settlements according to the landscape characteristics of their UPFs. The two principal components cover settlements at the four extremes of the landscape assessment of UPFs.
In the PCA ordination, the first two axes explained over 93% of the variance. These two axes describe the two major independent components of landscape structure in the area of 150 settlements representing municipal centres (Figure 8). Axis 1 describes a gradient from forested landscape on the left to the open space of agricultural landscapes with small remnants of forest patches on the right. Axis 2 is the gradient in the pattern of forest fragmentation. The bottom of the axis represents fragmented forest patches with a small proportion of core areas in the landscape, whereas the top represents settlements at the junction between open agricultural space and larger complexes of less fragmented forest.
On the right-hand side of the principal component PC1 is Odranci (Figure 5b and Figure 8), the municipality with the smallest proportion of forest, no core areas of forest patches, and the largest proportion of open agricultural space. At the far-left edge of this component is the centre of the municipality of Solčava, which lies in an area of forested landscape in the Kamnik-Savinja Alps. The settlement has an estimated forest cover of 77% within the area defined by walking distance, and core forest areas account for 55% of the total forest cover in this area.
At the extreme end of the second principal component PC2 lies the centre of Grad municipality, characterised by the typical landscape of Goričko in the Pomurje region, with a high proportion of forest within the settlement (51%) and fragmented forests with only 17% of the core area embedded in the agricultural matrix. At the other extreme of the PC2 component is Brezovica, 10 km from the centre of Ljubljana, on the edge of the open agricultural land of the Ljubljana Marshes and a condensed part of the forest matrix of the Polhograjsko Hills. Open agricultural land with a distance of more than 500 m from the forest core area dominates the area within walking distance of the settlement. Low forest cover (33%) was estimated because only the northern part of the settlement borders forests with a high proportion of core areas (71%).
The described gradients of landscape structure and fragmentation have been verified by forming separate groups of settlements with similar UPF characteristics within each group. The results of the principal component analysis (Figure 8) and k-means clustering method (Figure 9) are complementary. Clusters were formed on the basis of variables that contribute a significant loading to PC1 (Figure 10).
The baseline for estimating gradients in landscape structure and spatial characteristics of peri-urban forests was also tested for the 69 settlements with city status in Slovenia, which are described in more detail in Table 2 and Figure 6 and Figure 7. In the areas within walking distance, the two principal components of the PCA explained 69% and 23%, respectively, for a total of 92% of the variability (λ1 = 4.2 and λ2 = 1.4).
The gradient on the first PCA axis for 69 Slovenian cities captures (i) the landscape structure with a low proportion of forest patches in the three coastal cities (Koper, Piran, Izola) and those in agricultural landscapes (Žalec, Murska Sobota, Lendava, Brežice), and (ii) the Slovenian cities located on the edge of agglomerated forest complexes. The second principal component illustrates the same gradient already described for smaller Slovenian towns—from suburban forests with a low proportion of core areas in a landscape-diverse structure to towns at the junction between open agricultural space and larger complexes of less fragmented forest.

4. Discussion

This research investigates the landscape characterisation of Slovenian UPFs and enable their comparison despite the different administrative levels to which cities and settlements belong. Based on parameters of landscape structure and its fragmentation, it is possible to assess importance and accessibility of UPFs within different regional administrative units. However, when comparing the characteristics of UPFs within the country or with other countries, we encounter many obstacles, despite available spatial data sets harmonised at the European level. The Urban Atlas [52] provides data for the largest cities in the European Union, including the two largest Slovenian cities, Ljubljana and Maribor. We could not use it because both urban areas are delineated according to administrative city boundaries, which do not correspond to urban areas. Zepp et al. [36] have shown that it is inappropriate to estimate urban green space provision and accessibility within administrative city borders because they are highly arbitrary and they do not follow the spatial structure of urban areas.
Even at the level of individual Slovenian settlements, the new housing areas were discontinuous or dispersed and have experienced urban sprawl, which for many settlements is not represented consistently on either the CLC map or the Slovenian land use map. We had to delineate a third of the municipal centres ourselves based on the interpretation of digital orthophotos. In order to enable a comparison of UPFs within or beyond the country, we estimated the spatial characteristics of landscape units and forest patches based on already established recommendations in the assessment of landscape structure [10,45]. Assessment of the landscape structure and its fragmentation exceeds the boundaries of local administrative units. The assessment of landscape structure gradients and spatial characteristics of forests within settlements and cities offers opportunities for integrating landscape ecological baselines into UPF spatial planning. In view of urbanisation processes and the fragmentation of landscape units by infrastructure corridors, especially at the level of local communities, the demands of many stakeholders in cultural landscapes have not always been met so far [53]. For this reason, we estimated the gradients in an UPF structure according to the PCA and complementary k-means clustering. The starting points resulting from the assessed gradients can be considered when planning possible land-use changes within towns and cities and when creating new infrastructure corridors linking settlements.
Assessing gradients in an UPF structure is similar to many proposals that consider urban greenspace to have an important role for urban residents [54]. Examples of such typification range in spatial scale from, for example, informal urban greenspace-like derelict land, wasteland and road or railway margins as a segment of the natural environment in cities [55] to the assessment of relatively wild urban greenspaces and their biodiversity [56]. The common goal of all such approaches is to contribute to biodiversity conservation in urban regions and its better integration into urban planning.
We have considered UPFs with very different criteria, following the definition given in the introduction, which defines UPFs not only as forests adjacent to metropolitan areas, but also adjacent to smaller, rural settlements [23]. At both spatial levels—urban settlements and local municipal centres—we used a gradient of variables to highlight the unfavourable landscape structure of coastal towns and settlements in agricultural landscapes, where patches of forest with a small proportion of core areas persist alongside smaller patches of forest.
On the one hand, Slovenia has successful examples of the integration of UPFs into the sustainable management of cultural landscapes, as demonstrated, for example, in international awards and projects for the major cities of Ljubljana [57,58] and Celje [59], where the urban forest has already become a recognisable brand. On the other hand, many cities and smaller municipalities, with a desire to develop and maintain settlements, have converted agricultural land and forest into business zones with a lack of strategic planning at the level of landscape units [53], which contributes to fragmentation and a reduction of the forest’s inner environment and its accessibility. In the last decades, there has been a growing awareness of the importance of UPFs in local communities, including in regions with lower forest cover and higher fragmentation (Figure 4). Cities around the world have greater difficulties in providing access to urban forests and even to other green spaces in the city, with the average distance being more than 1 km [60,61]. The authors highlight new residential areas in larger cities as particularly problematic, suggesting the need for better urban planning also in terms of accessibility to green spaces. At the same time, the process of urban sprawl and de-urbanisation is important in Europe [62,63], which can also be illustrated by Slovenian urban sprawl and the continuous increase of small urban centres in the countryside.
Large differences in landscape fragmentation within regional units (Table 2) highlight the importance of spatial planning that cannot be based solely on general recommendations on sustainable management, but rather on adapting to the individuality of the landscape and thus of each UPF, which is the result of the interplay between historical tradition, specific location, urban development, and the visibility of the forest functions that the city uses and needs.
The first reports on the fragmentation of landscape units in different European regions [6] revealed surprising findings at regional levels, especially for Slovenia, where already high forest cover is thought to have a consequential influence on the maintenance of connectivity and natural processes in the landscape. NUTS-X regions with the highest levels of fragmentation are located in Belgium, the Czech Republic, Denmark, France, Germany, Luxembourg, the Netherlands, Poland, the United Kingdom, and Slovenia [6]. Comparable measures of landscape fragmentation across Europe support spatial planning policy for biodiversity conservation and encourage improvements in landscape quality. For use at the regional and local level, international comparisons are for information only. More detailed analyses of landscape structure and its fragmentation due to land-use change and the construction of local transport corridors are necessary to provide practical guidance for land-use planning and decision-making processes at the city level [5]. The assessments of core areas of forests near Slovenian cities (Table 2) suggest that the assessment of UPF could also be based on the recommendations that have been made for assessing landscapes to support as many area-sensitive species as possible [10]. In spatial planning, it can be assumed that a watershed or other land unit should have at least one, and preferably several, 200-hectare forest patches (measured as forest area more than 100 m from an edge).
Such core areas of forests preserve the habitats of fauna and flora in landscape units even near the largest cities. Extensive forest areas provide a greater diversity of habitat types and ensure habitats for more space-demanding animals. The minimum patch area requirements for species are highly dependent on species, quality of habitat, and landscape context. Van Dorp and Opdam [9] have found in the Netherlands that only forest patches larger than 10 ha support area-sensitive forest birds. More recent recommendations set this area threshold even higher [10,33]. By applying such recommendations, it is possible to preserve some of the natural processes that are characteristic of forested landscapes in urban and peri-urban areas.
Forest management plans are an important starting point for defining the ecosystem services of forests near settlements, but their role as urban and peri-urban forests is rarely defined in relation to local communities. The forests of these settlements are characterised by the allocation of a greater number of UPF-specific functions in forest management plans and by the greater number of forest learning trails. Despite the many defined functions of forests near settlements in Slovenia, only 17 settlements have been designated as UPF by the Special Purpose Forests Act. Most of these settlements have a population of less than 15,000 inhabitants. Slovenian towns that do not have this legal act in place, but where the importance of UPF is nevertheless recognised, follow other binding documents in their spatial planning that give these forests special significance. Examples are the defined green belt systems and rings of cities, which include not only forests but also other green and open areas, or recreation plans in the natural surroundings of the cities.

5. Study Limitations and Further Applications

Despite the small size of the Slovenian cities and settlements, the presented characterisation of settlements according to fragmentation and the depth of the UPFs’ inner environment can serve as a comparison, at least at the regional and the municipal levels of different countries.
When defining the UPF of a particular site, the presented research can provide a basis for further refinement of UPF planning and management. However, detailed analyses of forest functions, accessibility, and other factors that may influence UPF management at the local level are also needed.
In our case, we did not distinguish between urban and peri-urban forest patches. In some cases, it may be beneficial to have separate management and governance arrangements for urban and peri-urban forests, in order to address the specific challenges and opportunities of each type of forest. For example, urban forests may require more intensive management and monitoring due to their exposure to pollution, pests, and vandalism, while peri-urban forests may need to balance conservation and production objectives, such as timber harvesting and game management. In other cases, it may be more appropriate to have an integrated approach to UPF planning and management that takes into account the interdependent relationships between urban and peri-urban forests, as well as the wider landscape context. Ultimately, the most effective and sustainable approach to UPF planning and management will depend on a range of factors, including the ecological, social, economic, and political context of each region. Landscape ecologists can make a paramount endorsement to the quality of spatial planning and urban forestry applications. Maintaining and restoring the favourable landscape structure of UPF requires a coherent spatial policy and planning at all levels.

Author Contributions

Conceptualization, D.H. and M.N.; methodology, D.H. and M.N.; software, D.H. and M.N.; validation, D.H. and M.N.; formal analysis, D.H. and M.N.; investigation, D.H. and M.N.; resources, D.H. and M.N.; data curation, D.H. and M.N.; writing—original draft preparation, D.H. and M.N.; writing—review and editing, M.N.; visualization, D.H. and M.N.; supervision, M.N.; project administration, D.H. and M.N.; funding acquisition, D.H. and M.N. All authors have read and agreed to the published version of the manuscript.

Funding

This research was funded by the Slovenian Research Agency and by the Pahernik Foundation, Slovenia.

Data Availability Statement

The data presented in this study are available on request from the corresponding author.

Conflicts of Interest

The authors declare no conflict of interest. The funders had no role in the design of the study; in the collection, analyses, or interpretation of data; in the writing of the manuscript; or in the decision to publish the results.

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Figure 1. Slovenia is presented on the shaded relief of the Digital Elevation Model over Europe and the forest map [39]. The largest cities are marked along the network of highways, major roads, and railways (LJ—Ljubljana, MB—Maribor, CE—Celje, KR—Kranj, VE—Velenje, KP—Koper, and NM—Novo mesto).
Figure 1. Slovenia is presented on the shaded relief of the Digital Elevation Model over Europe and the forest map [39]. The largest cities are marked along the network of highways, major roads, and railways (LJ—Ljubljana, MB—Maribor, CE—Celje, KR—Kranj, VE—Velenje, KP—Koper, and NM—Novo mesto).
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Figure 2. The number of Slovenian municipalities (N, light grey bars) and the number of residents (dark grey bars) according to area classes into which individual municipalities were classified.
Figure 2. The number of Slovenian municipalities (N, light grey bars) and the number of residents (dark grey bars) according to area classes into which individual municipalities were classified.
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Figure 3. An assessment of landscape structure and fragmentation based on network of transportation corridors, built-up areas, forest and agricultural land is illustrated.
Figure 3. An assessment of landscape structure and fragmentation based on network of transportation corridors, built-up areas, forest and agricultural land is illustrated.
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Figure 4. The assessment of forest fragmentation (top) and forest cover (down) in the Slovenian regions and municipalities is illustrated.
Figure 4. The assessment of forest fragmentation (top) and forest cover (down) in the Slovenian regions and municipalities is illustrated.
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Figure 5. Forest cover in the municipalities of the Pomurska region. The two smallest municipalities, encompassing only one settlement each ((a)—Kobilje, (b)—Odranci) and the regional centre ((c)—Murska Sobota), as shown by the Sentinel-2 satellite image (Copernicus, 2022).
Figure 5. Forest cover in the municipalities of the Pomurska region. The two smallest municipalities, encompassing only one settlement each ((a)—Kobilje, (b)—Odranci) and the regional centre ((c)—Murska Sobota), as shown by the Sentinel-2 satellite image (Copernicus, 2022).
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Figure 6. Average walking distances to forest patches with an inner forest environment (a) and share of such core areas (b) in the total area of forests within walking distance around 69 Slovenian cities are presented. The largest black dots represent Ljubljana and Maribor, smaller black dots represent cities with more than 5000 inhabitants (36 cities, KP—Koper, KR—Kranj), grey dots more than 3000 (22 cities) and circles are cities with less than 3000 inhabitants (9 cities).
Figure 6. Average walking distances to forest patches with an inner forest environment (a) and share of such core areas (b) in the total area of forests within walking distance around 69 Slovenian cities are presented. The largest black dots represent Ljubljana and Maribor, smaller black dots represent cities with more than 5000 inhabitants (36 cities, KP—Koper, KR—Kranj), grey dots more than 3000 (22 cities) and circles are cities with less than 3000 inhabitants (9 cities).
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Figure 7. The share of forest core area (measured as interior forest area that is more than 100 m from an edge) and share of non-forested areas more than 500 m away from the interior area of forest patches within walking distance around 69 Slovenian cities are presented. The largest black dots represent Ljubljana and Maribor.
Figure 7. The share of forest core area (measured as interior forest area that is more than 100 m from an edge) and share of non-forested areas more than 500 m away from the interior area of forest patches within walking distance around 69 Slovenian cities are presented. The largest black dots represent Ljubljana and Maribor.
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Figure 8. Principal component analysis plot shows the multivariate variation among 150 settlements–municipal centres in terms of landscape structural variables within 1 km walking distance from the urban areas. Vectors indicate the direction and strength of each variable to the overall distribution (FC—forest cover, FCA—share of forest core areas that are more than 100 or 250 m from an edge, OSA—share of intensive agriculture open space, OS—share of areas more than 250 or 500 m from interior area of forest patches). Letters represent the extreme points of variability (a—Solčava, b—Odranci, c—Brezovica, d—Grad). The first two principal axes explained 93% of the variance (λ1 = 4.3 and λ2 = 1.3).
Figure 8. Principal component analysis plot shows the multivariate variation among 150 settlements–municipal centres in terms of landscape structural variables within 1 km walking distance from the urban areas. Vectors indicate the direction and strength of each variable to the overall distribution (FC—forest cover, FCA—share of forest core areas that are more than 100 or 250 m from an edge, OSA—share of intensive agriculture open space, OS—share of areas more than 250 or 500 m from interior area of forest patches). Letters represent the extreme points of variability (a—Solčava, b—Odranci, c—Brezovica, d—Grad). The first two principal axes explained 93% of the variance (λ1 = 4.3 and λ2 = 1.3).
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Figure 9. Determination of clusters into which 150 Slovenian settlements–municipal centres are grouped according to landscape variables within 1 km walking distance from the urban areas. Letters represent the extreme positions of settlements in clusters (a—Solčava, b—Odranci, c—Brezovica, d—Grad).
Figure 9. Determination of clusters into which 150 Slovenian settlements–municipal centres are grouped according to landscape variables within 1 km walking distance from the urban areas. Letters represent the extreme positions of settlements in clusters (a—Solčava, b—Odranci, c—Brezovica, d—Grad).
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Figure 10. Empirical statistics derived from PCA test analysis of six variables measured for cities (a) and settlements (b) in Slovenia are presented. All variables have significant contribution on PC1 (1—intensive agriculture open space; 2, 3—share of areas more than 250 or 500 m from interior area of forest patches; 4—forest cover; 5, 6—share of forest core areas more than 100 or 250 m from an edge).
Figure 10. Empirical statistics derived from PCA test analysis of six variables measured for cities (a) and settlements (b) in Slovenia are presented. All variables have significant contribution on PC1 (1—intensive agriculture open space; 2, 3—share of areas more than 250 or 500 m from interior area of forest patches; 4—forest cover; 5, 6—share of forest core areas more than 100 or 250 m from an edge).
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Table 1. List of the variables analysed in the landscape units and UPF fragmentation.
Table 1. List of the variables analysed in the landscape units and UPF fragmentation.
AbbreviationVariable Description
AWMArea-weighted mean patch size of landscape units surrounding each city
Depth UAMaximum distance from urban area boundaries to urban core areas
FCForest cover in landscape units surrounding each city
Core RMaximum distance to forest core area, forest area fragmented with local roads
Core FMaximum distance to forest core area, forest area fragmented including forest roads
FFShare of forest functions in the forest area of landscape units surrounding city
FCA100Share of forest core areas that are more than 100 m from the edge of a forest patch
FCA250Share of forest core areas that are more than 250 m from the edge of a forest patch
OSAShare of intensive agriculture open space
OSA250Share of open space areas more than 250 m from the interior habitat of forest patches
OSA500Share of open space areas more than 500 m from the interior habitat of forest patches
Table 2. Landscape and forest features in the vicinity of the largest Slovenian cities are presented.
Table 2. Landscape and forest features in the vicinity of the largest Slovenian cities are presented.
Code 1CityUrban Area (km2)Inh 2
(1000)		AWM 3
(km2)		FC 4
(%)		Core 5 R (m)Core 5 F (m)FF 6
(%)		Forest Functions 7
1Murska Sobota4.0011.02.0112.425324794.4C B H
2.1 Maribor24.8197.021.8751.580442439.8C E R H
2.2 Ptuj5.4318.012.8920.137929069.3B C E R
2.3 Slov. Bistrica3.478.24.0934.644943150.2C
3.1 Ravne2.087.22.8862.632729853.0C P PH
3.2 Slov. Gradec2.267.36.2649.646846038.3C P H
4.1 Celje *9.7637.45.6345.844530831.0C E R B
4.2 Velenje *7.4025.54.7044.341039452.4R E C P H
5.1 Zagorje1.486.08.5667.948241553.8P C R B
5.2 Trbovlje3.3913.77.4567.133631661.7P C R PH H
5.3 Litija1.636.818.4671.491658110.5P PH H E B
6.1 Krško4.246.88.0739.969552038.2H C B P PH R E
6.2 Brežice2.206.95.267.315614591.8B P C H
7.1Kočevje2.588.1140.6686.7204278925.6B H C P E R
7.2Novo mesto *6.5123.96.2956.894759032.1B C E R PH
8.1Kamnik3.6713.99.8573.475245342.2P R PH C H B
8.2Mengeš1.617.024.3562.2103856057.0P R C E H PH B
8.3Domžale5.0913.18.6920.565361181.4P PH B C E
8.4Ljubljana *59.76285.619.9536.574572068.3R B E C P H PH
8.5Grosuplje1.687.61.4828.833829671.0B C R
8.6Vrhnika3.148.98.5556.058029268.7R P B H
8.7Logatec2.899.912.0770.499354740.0B C P H R PH
9.1Jesenice4.8313.5122.6577.784262665.0P H C B R E
9.2Kranj *7.5538.020.7661.2132674442.5C B E P H R
9.3Škofja Loka2.1711.717.1576.993074629.8P C E H R
10Postojna2.689.716.2358.6113172456.8B C H E P
11.1Ajdovščina2.076.916.8756.445939161.1B C P H
11.2Nova Gorica *5.1912.95.9875.266045077.0C E H R
12.1 Izola2.1211.80.9514.313312596.1B E C R
12.2Koper5.6726.014.2422.921920837.3B C R
1 Code represents the serial number of the city and its affiliation to a particular NUTS-3 region. 2 Inh—number of inhabitants per city in 1000; 3 AWM—weighted mean patch size surrounding the cities; 4 FC—forest cover (in landscape fragmentation units); 5 Core area (R—fragmented from local roads without forest roads; F—fragmented including forest roads); 6 FF—share of forest functions; 7 Forest functions—B biotopic, C climate (and hygienic-health), E aesthetic, H hydrological, P protection of forest soils and stands, PH protection of cultural heritage, R recreational, educational and research). * Cities with the designated UPF by the Special Purpose Forests Act.
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MDPI and ACS Style

Hladnik, D.; Nastran, M. Landscape Structure and Fragmentation: Key Factors in the Characterisation of Urban and Peri-Urban Forests in Slovenia. Land 2023, 12, 1968. https://doi.org/10.3390/land12111968

AMA Style

Hladnik D, Nastran M. Landscape Structure and Fragmentation: Key Factors in the Characterisation of Urban and Peri-Urban Forests in Slovenia. Land. 2023; 12(11):1968. https://doi.org/10.3390/land12111968

Chicago/Turabian Style

Hladnik, David, and Mojca Nastran. 2023. "Landscape Structure and Fragmentation: Key Factors in the Characterisation of Urban and Peri-Urban Forests in Slovenia" Land 12, no. 11: 1968. https://doi.org/10.3390/land12111968

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