Connectivity as a tool in the prioritization and protection of sub-urban forest patches in landscape conservation planning

Landscape and Urban Planning 153 (2016) 129–139

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Research paper

Connectivity as a tool in the prioritization and protection of sub-urban forest patches in landscape conservation planning Janez Pirnat ∗ , David Hladnik University of Ljubljana, Department of Forestry and Renewable Forest Resources, Vecna pot 83, 1000 Ljubljana, Slovenia

h i g h l i g h t s • • • • •

The structure of forest patches and their spatial distribution are benevolent. Spatial distribution of urban forests in Ljubljana is still favourable. The real fragmentation occurred during the construction of the highway beltline. Connectivity changes and nature preservation can be presented by a spatial model. Connectivity among forest cores is an important index of habitat conditions.

a r t i c l e

i n f o

Article history: Received 15 September 2015 Received in revised form 6 May 2016 Accepted 13 May 2016 Keywords: Connectivity Forest patches Graph theory Habitat network model Sub-urban

a b s t r a c t Urbanisation development influences surrounding landscape processes, which are reflected by landscape structural patterns. Forest areas are often regarded as a spatial reserve for present and future urbanisation needs, while at the same time they often represent the last remnant of natural environment. In the present research we analysed (1) the change in forest cover in the area of suburban forests of Ljubljana between 1975 and 2012, (2) the connectivity and conservation buffers as one of the foundations for the assessment of biodiversity functions. Between 1975 and 2012, all the forests with important cores were subject to clearings for settlement- and agricultural purposes, but clearing usually did not extend beyond forest edges. The real fragmentation occurred during the construction of the highway beltline. In the area of Ljubljana, connectivity changes and connectivity loss in two different time periods are presented by a spatial model based on the Graph Theory which can also be used in spatial planning. Due to the high percentage of forest cover and the favourable distribution of forest patches and cores around the city of Ljubljana, no connection is currently in danger; the weakest link is stretching from the centre of Ljubljana towards the southeast. In the process of evaluating the biodiversity of urban forests, it will be necessary to add connectivity among forest cores as an important index while evaluating the favourable conditions of different habitat types. © 2016 Elsevier B.V. All rights reserved.

1. Introduction 1.1. The pressure on urban forests Urban forests have an essential influence on the relations between urban population and nature. However, urban and infrastructural expansion causes dramatic changes in numerous urban landscapes. Several forces driving landscape change can be identified (Bürgi, Hersperger, & Schneeberger, 2004): socioeconomic

∗ Corresponding author. E-mail address: [email protected] (J. Pirnat). http://dx.doi.org/10.1016/j.landurbplan.2016.05.013 0169-2046/© 2016 Elsevier B.V. All rights reserved.

forces, political initiatives, technology, natural forces, and cultural forces. Urbanisation development influences surrounding landscape processes, which are reflected by landscape structural patterns (Ode & Fry, 2006). Urban influence has increased the extent, intensity (Ode & Fry, 2006) and irreversibility of changes (Kasanko et al., 2006). In an urban society, natural ecosystems are important for various ecosystem services (Daily, 1997; Dobbs, Escobedo, & Zipperer, 2011; Hladnik & Pirnat, 2011; Konijnendijk, 2008) habitat support and resource regulation (De Groot, Alkemade, Braat, & Willemen, 2010). In urban areas with extensive forest cover, many of these ecosystem services are supported and provided by urban and suburban woodlands. Their proximity to natural structures seems to be one of the most important woodland elements

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providing different social (amenity, recreation) ecosystem services (Caspersen & Olafsson, 2010) and ecological (biodiversity) ecosystem services (Konijnendijk, Nilsson, Randrup, & Schipperijn, 2005; Konijnendijk, 2008; Hladnik & Pirnat, 2011). Urban demand for the construction of roads, railroads and other infrastructure in city development is facing growing pressure on supporting ecological services, especially on biodiversity. Within the context of these two often contradictory interests, the main objective of researchers and landscape planners has been to identify and preserve key elements or biotopes supporting pristine areas and their connectivity within a landscape (Forman & Collinge, 1997; Gagné et al., 2015; Kubeˇs, 1996; Löfvenhaft, Björn, & Ihse, 2002; Rudnick et al., 2012). Enhancing key elements from strategic points into a pattern of crucial ecosystems is considered the best strategy for reducing, or at least mitigating negative effects on forest fragmentation (Forman & Collinge, 1997; Kubeˇs, 1996; Saura, Estreguil, Mouton, & Rodriguez-Freire, 2011). Connectivity loss represents one of the major threats to the preservation of biotic diversity in natural ecosystems (Pascual-Hortal & Saura, 2008). 1.2. Conservation buffers and habitat networks in green infrastructure According to Forman (2008), green infrastructure represents a network of natural corridors and patches. The habitat connectivity provided by urban green areas is supporting biodiversity in urban areas (Kong, Yin, Nakagoshi & Zong, 2010). Green infrastructure fragmentation results in habitat loss and the depletion of different types of ecosystem services (Cambridgeshire Green Infrastructure Strategy, 2011; Weber, Sloan, & Wolf, 2006). It was shown that in most urban areas in Europe the woodlands are being fragmented and destroyed, the urban forest is mostly in decline (Pauleit, Jones, Nyhuus, Pirnat, & Salbitano, 2005). Habitat loss as a result of direct human impacts can be measured in two ways. The first is a direct reduction in area (sometimes it is important to distinguish reductions in core area vs. total area) and the second is reduction in the connectivity between the most vital landscape habitats and elements along with an increasing proportion of edge area vs. total area. Large areas of natural vegetation with a significant amount of core area are usually more efficient in providing optimal shelter and habitat for the majority of interior species populations (Weber et al., 2006). Unfortunately, it is impossible to categorise and summarise all of the previously conducted research on the meaning and influence of landscape structure on the preservation of habitats and landscape processes as narrowly as planners in charge of urban and suburban environments desire. In many science-based guidelines provided to assist decisionmakers involved in natural heritage planning and landscape conservation, umbrella species (sensu Breckheimer et al., 2014) and predominant bird species are often used as indicators of landscape quality. Because birds are more easily surveyed, knowledge of their habitat requirements and distribution is supposedly greater than for other wildlife (Environment Canada, 2013). In biodiversity conservation, the use of umbrella species whose conservation ensures the protection of a large number of co-occurring species has been critically examined (Roberge & Angelstam, 2004). Branton and Richardson (2011) argued that additional empirical testing is also needed. Nevertheless, the potential for umbrella species has been recognised and the concept has been further developed and refined. In contrast, and in line with recommendations for further development of species as indicators, a pan-European study of biodiversity in agricultural landscapes (Billeter et al., 2008) indicated that no single species group emerged as a good comprehensive indicator of other species groups. The results indicated that preserving

and, where possible, increasing the semi-natural habitat can stop the loss of biodiversity in these landscapes. In agricultural landscapes, the largest contribution to total biodiversity is from natural and semi-natural habitats and is significantly influenced by their area. It has been stressed that the nature of the matrix can have a profound effect on habitat use by different species, particularly in highly fragmented urban and rural landscapes in different countries (Environment Canada, 2013). In case of small mammals the habitat size and level of isolation are two of the key determinants of species composition (Vieira et al., 2009). Despite the ecological paradigm that habitat corridors connecting isolated habitat patches will increase the abundance and diversity of species within those patches by facilitating increased rates of movement, Davies and Pullin (2007) indicated that empirical evidence was not sufficient to support the effectiveness of hedgerow corridors as a conservation tool to promote viability of woodland fauna populations. Based on a rigorous systematic review, they estimated that the available information is insufficient to make adequate recommendations that are needed by practitioners and policy-makers. However, in favour of the afore-mentioned prevailing studies on mammals, birds and invertebrates, the assumption that corridors facilitate exchange of organisms has been proven for the pollinators because the corridors are important for maintaining genetically viable plant populations (Townsend & Levey, 2005). Bentrup (2008) stressed that there are still many gaps in our understanding of conservation buffers as represented by wildlife corridors, greenways, windbreaks, and filter strips along with their ecological and socioeconomic impacts on rural and urban landscapes. However other researchers agree that different and often intraconnected ecological consequences of habitat loss and fragmentation can be understood and measured on the basis of the concept of connectivity (Laita, Kotiaho, & Mönkkönen, 2011). A guide for planners should not serve as the sole source of design information but rather as a means to facilitate and communicate the design process to optimise benefits and minimise potential deleterious impacts. The role of conservation buffers in landscape structure has been estimated to provide benefits for nature (water quality, biodiversity, soils), society (economy, employment) and culture (aesthetics and visual quality, outdoor recreation). The multifunctionality of landscape and forest management focuses on the integrity of a very broad range of ecosystem services, which are required to fulfil different roles at different scales, ranging from forest stand to landscapes (Lafortezza, Chen, Sanesi, & Crow, 2008; Saura, Estreguil et al., 2011; Saura, Vogt, Velázquez, Hernando, & Tejera, 2011); furthermore, these have to be included in planning sustainable landscape management (De Groot, 2006). Given that a continuous urbanisation is an inevitable reality, it is very important to develop landscape conservation programs directed towards strategic conservation of the most important and valuable landscape elements and ecosystems (Weber et al., 2006; Forman & Collinge, 1997). 1.3. The significance of urban and suburban forests in Ljubljana and the aims of the study In Slovenia, the scientific community and municipalities are increasingly aware of the significance of urban forests. In 2010, the Municipality of Ljubljana passed a Decree for Special Purpose Forests, which, in principle, protects existing forest cover. However, the co-existance of infrastructure programs and agricultural policy, makes it unrealistic to expect that this administrative criterion would be sufficient by itself to prevent forest clearances. It is also necessary to ensure the diversity of urban forests, not only within forest areas protected by the above-mentioned decree but also on a broader landscape level, represented by landscape subunits on the central Slovene plane (Fig. 1a)—the most populated

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Fig. 1. (a) A map of the study area in the central Slovenian plane with marked landscape subunits (solid line) of the Kranj-Sora Plain (LU1), the city of Ljubljana (LU2) and Ljubljansko Barje plain (LU3). Dashed lines represent the borders of study area. The background is derived from Landsat TM imagery acquired over Slovenia in 2010. (b) Broader study section of Ljubljana with a municipality border and a central area within the highway ring road (bold black line) and proposed Baltic–Adriatic Rail Freight Corridor 5 (dashed line). The forests (dark grey) are presented for estimating the open space and a connectivity analysis in the urban areas (white) and on the agricultural landscape (light grey).

area in Slovenia. The Kranj-Sora Plain (LU1) forms the extensive flat area, densely populated and covered with cultivated fields and woods. The largest urban area of Slovenia is located in the Ljubljana Basin. Beyond the city of Ljubljana (LU2) spreads the landscape park Ljubljansko barje (the Ljubljana Moor), boggy area with grasslands, woodlands, fields, ditches and hedges (LU3). The central part of Ljubljana is enclosed by the highway ring road, which was built between 1979 and 1999 (www.dars.si). Several forest patch areas were fragmented due to this ring road construction. Another threat to forest patch connectivity represents the proposed Baltic–Adriatic Rail Freight Corridor 5 which will connect ports in Poland, Czech Republic, Slovakia, Austria, Slovenia and Italy (Ec Europa, 2015). Ljubljana railway hub represents the meeting point of the European rail corridor. Its variants are shown in Fig. 1b (dashed), and it is worth noting that they will be placed straight in the junction of natural and urban areas around the capital. The importance of the integration of the most valuable parts of nature in the network has been recognised (LUZ, 2010). Contact between the town and the green hinterland will be maintained with green wedges. Therefore, it is crucial to identify major green areas which require the establishment of links between individual areas of green and open public spaces as well as links to the hinterland of the city. Therefore following research questions were examined: 1. How forest clearances in the urban and suburban area of Ljubljana between 1975 and 2012, (namely during the period of

highway corridor and urbanisation construction) influenced forest connectivity? 2. Which of the forest patches in urban and suburban landscapes are the most important within a network of connectivity as a support for the assessment of biodiversity forest functions and the key elements for preserving forest cover and the diversity of urban environment especially in the frame of future changes? The forests protected by the above-mentioned decree are well preserved (Hladnik & Pirnat, 2011). Up-to-date research is rather thorough in covering the recreational role of these forests, but is less comprehensive in discussing their role in biodiversity, especially at the landscape level. Consequently, new methods for assessing connectivity are based on graph theory and have recently been developed (Gurrutxaga, Rubio, & Saura, 2011; Pascual-Hortal & Saura, 2008; Saura, Estreguil et al., 2011; Saura, Vogt et al., 2011; Zetterberg, Mörtberg, & Balfors, 2010). In this research, we would like to emphasize the importance of protecting forests patches based on their functional connectivity. 2. Data and methods 2.1. Study area and spatial data information Ljubljana is situated in flat area of the Ljubljana Basin from 290 m a.s.l., surrounded by a hilly forested landscape up to 700 m a.s.l. Forests represent the most dominant ecosystem in Ljubljana and

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Fig. 2. Overall relative open space (Or OS) and distance to the forest edge and natural vegetation remnants in the city of Ljubljana (LU2) and two neighbouring landscape subunits.

its surrounding suburbs (Hladnik & Pirnat, 2011). Forests occur on hilly surroundings, whereas forest patches on the plains are remnants of former hornbeam and oak forests. Extensive tree-and shrub vegetation is preserved alongside waterways. To analyse open space and the connectivity of forest patches on the central Slovene plane, the landscape regionalisation of Slovenian landscape types was used (Maruˇsiˇc, Ogrin & Janˇciˇc, 1998). The borders of landscape types were aligned with settlements and road corridors running along the foothills and passing into the forested landscape. Spatial distribution and open space analyses were carried out on the landscape subunits, which are presented in Fig. 1a. A broader study section of Ljubljana with a municipal border and a central area within the highway ring road area presented in Fig. 1b and in Table 4. At the highest hierarchical level of landscape subunits, the connectivity and importance of natural vegetation remnants were assessed based on an actual land use map of Slovenia. An agricultural land use map from the Slovenian Ministry of Agriculture, Forestry and Food (2011) was used. This information on land use was supplemented by a forest stand map from the Slovenia Forestry Service with a scale of 1:5000 and a minimum mapping unit of 0.25 ha. Based on these datasets the overall relative open space area (Or OS) was calculated. The concept of the overall relative core area of forest patches in the landscape presented by Hennenberg, Orthmann, Steinke, & Porembski (2008) was modified by Hladnik and Pirnat (2011). The relationship between the total area (TA) of the landscape subunits and the buffer zones or distance belts was calculated for each of the 25 m distance steps measured from forest edge and natural vegetation remnants (Fig. 2). The overall relative open space area was plotted against the distance belts to estimate proximity to forests and, separately, to hedgerows, natural vegetation remnants and spontaneous afforestation on abandoned agricultural lands. The study area spans a rectangular section (30 km × 25 km) around Ljubljana that includes the city of Ljubljana and its suburbs. Forest clearances in the years 1975 and 2012 were visually detected

and delineated using digital orthophoto images from aerial surveying of Slovenia. Infrared and panchromatic digital orthophoto images were used for change detection and the verification of land use maps. Today, the largest share of land use (45%) is occupied by forests representing urban and suburban forests in Ljubljana (Table 1). In the central study area within the highway ring road urban forests cover 19% of the area. Public green areas such as parks, playgrounds and gardens were not delineated on the land use map. They cover 12% of the urban area and were described and analysed in the previous research (Hladnik & Pirnat, 2011; Pauleit et al., 2005). The included forests have been declared Special Purpose Forests, regardless of their structure, functions and their landscape role. Of the aforementioned 19% of forests, 15% are considered primeval forests that have a persistency based on a forest continuum as described by Hladnik and Pirnat (2011). 2.2. Graph theory and habitat network model The use of graph theory in landscape ecology has proven its value because graph structures turned out to be an effective tool for evaluating both landscape network pattern and analysis of connectivity on a landscape level (Pascual-Hortal & Saura, 2006, 2008). Our study was based on the assumption that central core areas of preserved forests are comprised of surfaces where forest diversity is best preserved and sustained because these forest segments are late successional, spatially stable and persistent based on a forest continuum. Consequently, all of the interior forest segments that were at least 250 m within the edges of forest patches or forest matrix were defined as core areas. Distance from a forest edge indirectly determines the smallest size of forest patches that includes species that are typical of the interior forest environment. The recommendation for the minimum patch size for various species differs, but it also depends on the quality of the habitat and on the landscape context. For wooded corridors and grasslands, the maximum edge effect has been observed at distances from 300 ft. to

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Table 1 Land use types in broader and central study area according to agricultural land use map from the Slovenian Ministry of Agriculture, Forestry and Food (2011). Land use type

Arable land Orchards and permanent crops Meadow Swamp meadow Uncultivated agricultural land Afforested agricultural Forest plantation Trees and shrubs Forest Swamp and marshy areas Open space with little or no vegetation Built-up and similar artificial surfaces Waters Total

Broader section around Ljubljana

Central area within the highway ring road

ha

%

ha

%

927.50 690.28 12802.83 3891.61 362.11 1124.80 14.02 1100.32 3374.2 32.67 21.71 11364.41 574.49 75000.00

12.37 0.92 17.07 5.19 0.48 1.50 0.02 1.47 44.99 0.04 0.03 15.15 0.77 100.00

234.20 16.55 357.17 105.66 10.66 59.43

4.21 0.30 6.42 1.90 0.19 1.07 1.26 19.29

1300 ft. (Bentrup, 2008). A distance of 250 m (820 ft.) from the forest edge forms a patch of at least 20 ha in a round or square shape. With the patch size, it is possible to predict the presence of species typical of the inner-forest environment since, according to the estimates, patches smaller than 20 ha are predominantly home to bird species tolerant of forest edges as summarised from various sources in Environment Canada (2013). All of the inner forest zones represented nodes, whereas all the remaining non-core forest surfaces and non-forest surfaces represented links according to graph theory. A connected region occurs when a set of nodes create a path between every pair of nodes. Consequently, the links stretch over different land use surfaces; this pattern determines the quality and suitability of the patch’s connectivity value. Measuring accessibility between nodes using Euclidean distance needs to be avoided for non-flying species because it is necessary to take into account the friction effect of different land-uses that might need to be crossed to move between nodes (Gurrutxaga et al., 2011). Therefore, it would make sense to categorise different land use types based on the level of difficulty they cause for various groups of animal species to move across the landscape. To evaluate the landscape matrix resistance for a group of forest mammals, values have been suggested by Gurrutxaga et al. (2011) and were used because they were derived from a wide literature review. According to the above-mentioned authors, these values range from 1 for forests, 5 for bushes, 15–40 for different agroforestry and pastures and meadow mosaics, 60 for crops, 100 for water bodies and 1000 for urban areas and highways. These values might also compensate changes in outer border of forest patches through clearances. Although the core forest areas remain the clearances can effect corridor movements of the animals. The effective distances between forest nodes were calculated using the Linkage Mapper programme (McRae and Kavanagh, 2011). Linkage Mapper uses vector maps of core habitats and raster maps of movement resistance to identify and map the least-cost linkages between the core areas. Each cell in the resistance map is provided with a value that marks how difficult it is to move across the cell. First Linkage Mapper finds adjacent core areas and creates a network of core areas using adjacency and distance data. Second, it calculates cost-weighted distances and least-cost paths; finally, it measures least-cost corridors and uses them to create a single map (for additional information see McRae & Kavanagh, 2011). We used Linkage Mapper to repeat the process of land use analysis in 1975 and 2012 and calculated the effective distances for each year. Next, we used the Conefor 2.6 programme (http://www. conefor.org.) to calculate the Probability of Connectivity (PC) for conditions in 2012 (Saura & Pascual-Hortal, 2007; Saura, Estreguil et al., 2011). The PC varies based on the position and characteris-

69.97 1072.94 0.25 3579.94 55.60 5562.37

0.00 64.36 1.00 100.00

tics of the habitat patches as well as on species mobility. The range varies from 0 to 1 and is given by the following formula: PC =

ni=1 nj=1 ai aj pi,j A2L

where ai and aj represent areas of habitats i and j, while AL stands for the entire study area comprised of both habitat- and non-habitat patches. The strength of each link is described by pij , which marks the probability of a direct dispersal between the patches i and j. Because the structure of the PC metrics has already been comprehensively described by several authors (Saura & Rubio, 2010; Saura, Estreguil et al., 2011), only a brief summary is given here. Saura and Rubio (2010) provided a more thorough description of the PC metric components and discussed the possibility of node importance values derived from this metric as evaluated through separate fractions (dPCintra, dPCflux and dPCconnector) that are used to specify different ways in which nodes contribute to habitat connectivity. dPCintra represents the connected area within the node (intrapatch connectivity). dPCflux measures the amount of dispersal flux that is estimated to spread between a particular focal node and the rest of the habitat areas in the landscape provided that the mentioned focal node is either the origin or the destination of the flux. dPCconnector analyses the contribution of a node to the connectivity between other nodes, using it as a point of connection or a stepping stone between them. As the mobility of different species of mammals varies significantly, we have adopted information from Wildermuth (1980), taking into account a median of 300 m as the average dispersal distance. The dispersal distance was multiplied by the median value of resistance on the friction surface. As a result, an effective distance threshold has been reached when it corresponds to a 0.5 dispersal probability between different nodes (Saura & Pascual-Hortal, 2007). In this way, we were able to obtain relative node- and link importance values for each of the nodes and links. In relation to this, we were interested in core forest areas representing the most significant nodes and in non-core forest areas representing important linkages. The spatial connectivity model was compared to observations and mapping of mammal- and bird distribution and density in Slovenia. The database for the red deer (Cervus elaphus), the wild boar (Sus scrofa), and the roe deer (Capreolus capreolus) density was prepared based on the central Slovene register of large game species (Jerina, 2012). It contains data on all the removed animals (i.e. hunter-killed, road-killed, and individual animals found dead occasionally) within 1 × 1 km grid cells. For the birds, no comparable data of the entire model area available.

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Table 2 Forest core areas – nodes – basic information. Core ID with highest dPCconnector node value

Number of core areas

Area (ha)

dPCconnector node value

11, 72 36, 39, 41, 44, 56, 62, 66, 73, 76, 81, 82, 92, 12, 37, 51, 64, 74, 83, 84, 90, 93, 94, 101, 102, 110, 112, 115, 116 other Core ID with low dPCconnector node value Total

2 12 16 96

2264.69 1972.74 1043.40 2947.60

0.16452–0.21334 0.01098–0.07136 0.00136–0.00952 0.00011–0.00001

126

8228.43

Table 3 The ten most important connectivity nodes based on different fractions. Rank

dPCintra Node no.

dPCintra Value

dPCconnector Node No.

dPCconnector Value

1 2 3 4 5 6 7 8 9 10

11 72 4 57 66 115 95 81 116 76

31.04909 17.18120 10.68947 3.145684 2.329645 2.167876 1.931933 1.923695 1.409081 0.892573

72 11 83 44 76 62 36 81 66 39

0.213338 0.164520 0.071363 0.065610 0.054846 0.046918 0.043451 0.034605 0.022098 0.021661

3. Results Half of the Ljubljana landscape subunit (LU 2) was estimated to be located up to 425 m from the nearest forests and three-quarters were estimated as located up to 725 m from the nearest forests. In the Barje plain (LU 3) three-quarters of urban and agriculture lands were located 450 m away from forests and 80% were less than 100 m from forests, hedgerows and natural vegetation remnants. These differences emphasise the importance of hedgerows and natural vegetation remnants within the landscape subunits of Ljubljana. When these elements were included in a spatial model, the distances from urban and agricultural lands to green infrastructure elements were reduced to less than 175 m for the half of the Ljubljana subunit.

of forest patches (here reflected by size) and their spatial distribution are valuable. Furthermore, it has been established that none of the above mentioned patches lies within areas protected by the decree passed by the Municipality as Special Purpose Forests. On the contrary, the most important dPC patches actually surround forests defined by the decree as “cloak”. These patches surround the city and maintain habitat connectivity on the landscape. Therefore, it can be concluded that to preserve connectivity and its diversity of the functions served by the Special Purpose Forests, these connections are of vital importance. No less important are the smaller forest patches that do not otherwise possess enough internal environments to function as nodes. Instead, they form vitally important connections as pass-through forests.

3.2. Estimation of forest clearances 3.1. Evaluation of node importance and connectivity In the central study area, a total of 126 nodes were obtained with core areas covering 8228.43 ha of forests or 26% of all forest areas or almost 12% of the entire surface. The rest of the forests as well as other forest areas and natural vegetation remnants represented links joining different nodes. More than 51% of all of the core areas reached the highest dPCconnector node values. This high percentage indicates that spatial distribution of forest patches with inner environments is still favourable despite their relatively low dPCconnector values, suggesting the possibility of transfer difficulties appearing in urban areas at a given distance. When dPCconnector is higher than 0, it represents a patch covering the most favourable »path« between two nodes or suggests other paths (connections) between the remaining patches that could not sufficiently fill the role of the given patch presumed to be cleared in the process of land use change (Table 3). From the 10 most important nodes in the dPCconnector fraction and the 10 most important nodes in the dPCintra fraction, as many as 5 of the nodes were found to be shared by the two fractions. As was noted in the method description, the dPCintra fraction is susceptible to influence by patch size; therefore, the largest forest patches were regarded as well. The dPCconnector, on the other hand, displays the most important patches functioning as steppingstones on the landscape. The fact that no less than 5 patches were common according to both criterion, emphasises that the structure

The relationship between clearances, afforestation areas, forest and other land uses in different sections from 1975 to 2012 are presented in Table 4. Until 2012, 66.44 ha of forests were cleared in the central area bounded today by the highway ring road. Most of the clearances were caused by construction of the highway ring road, which is now used to divide the central study area. Clearances for agricultural purposes represent 11.94 ha, with meadows serving as a prevalent land use in cleared areas. The categories “overgrowing agricultural land” and “trees and shrub” usually proved to be poorly chosen designations as they actually included highway greening, noise barriers and similar measures accompanying the construction of roadways. Water bodies were in fact ponds that appeared in the forest on Golovec hill. The largest share of clearances, however, was a result of changes due to urbanisation and included expansion of built-up areas, highways and other road construction. In the case of the two largest patches within the highway ring road (the hills of Roˇznik and Golovec), forest edges clearances have been observed, whereas for the smaller patches, the analysis indicated typical fragmentation (hence a smaller surface area for both larger patches), a decline in number of patches between 0.5 and 1 ha and a simultaneous increase in the number of patches below 0.5 ha. The effective connectivity between forest patches with significant inner cores did not visibly change at the landscape level from

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Table 4 Land use changes from 1975 to 2012. Type of change

clearing afforested forest remainder total

Broader section around Ljubljana

Municipality of Ljubljana

Central area within the highway ring road

ha

% of entire area

% of forest

ha

% of entire area

% of forest

ha

% of entire area

% of forest

−2593.02 +2860.82 30881.70 38664.46 75000.00

3.46 3.81 41.18 51.55 100.00

8.40 9.26

−892.35 +1257.31 10245.63 15103.40 27498.69

3.25 4.57 37.26 54.92 100.00

8.71 12.27

−66.44 +161.51 911.43 4422.99 5562.37

1.19 2.90 16.39 79.52 100.00

7.39 17.72

–

1975 to 2012. None of the observed patches disappeared, although their surface structure changed in some areas. Because clearances for urbanisation were carried out primarily as an expansion of already existing settlements on forest edges, unsuitable terrain and various ecosystem forest services prevented these processes from becoming too extensive or interfering with the preserved forest matrix cores. On the other hand, the process of clearance for infrastructure development was different. The construction of highways and some industrial zones contributed to local changes in links between individual inner core environments. The connectivity was similar in both periods in the northern part of the analysed area. The most significant cores (115, 116) remained connected to each other and to other cores in the same places; they even gained a connection due to an area of afforestation. It is interesting to note that a newly built industrial zone at the eastern side of the northern area did not break the connections because it did not reach the depth of core number 115. In the northeastern section, there were practically no changes due to the prevalence of smaller clearances and with no significant impact on the connectivity. Cores nr. 95 and 76 remained connected to each other and to other cores to more or less the same extent during both periods. The eastern part of the analysed area was the same, where the nr. 72, 44, 62, 39 and 36 cores retained similar connectivity. From place to place, some connections were lost due to clearances, but their role could be easily replaced with new connections made possible either by a relatively short distance between cores or by newly acquired afforested surface patches in vicinity. The connectivity of the south and west cores remained similarly unchanged, with the nr. 4 and 11 cores retaining the same connections to each other and to other cores. The same is true for the nr. 57, 60, 83 and 81 cores, where certain connections grew even stronger. The most significant changes occurred in the central part of the analysed area, where at the end of the 20th century, a highway ring road was built around the city of Ljubljana (Fig. 1b). Before construction, current core areas G1 and G2 were connected (Fig. 3), making a united core area with numerous connections through forests. After the construction of the highway ring road, a 400 m wide connection above the Golovec tunnel remained; however, the connections to the south were weakened (Fig. 3). Albeit weakened, a connection with the south is still possible as long as there are forested and extensive agricultural areas left on landscape. Any intensive urbanisation of this area, however, would strongly damage the connectivity (Fig. 4). 4. Discussion In the area of Ljubljana, the connectivity changes and connectivity loss during two different time periods from 1975 to 2012 were represented by a spatial model that can be used in spatial planning. Our results can help landscape planners to identify and analyse critical elements changing over a landscape. Given the small share of forest clearances over the last 30 years (Table 5), a crucial requirement of urbanisation processes on a suburban landscape is the determination of critical points in space that preserve habitat connectivity in urban and suburban forests. As estimated

–

–

Table 5 Forest clearing in central of Ljubljana according based on purpose. Forest in 1975 (ha)

Cleared until 2012

Clearing purpose

0.60 0.34 10.77 0.23 9.52 1.72 42.96 0.30  66.44

agricultural

field orchard meadow swamp meadow afforested agricultural trees and shrub built-up and similar waters

11.94 protection belts 11.24 42.96 0.30  66.44

by Li and Wu (2004), interpreting landscape connectivity and connectivity indices pose difficulties due to poor understanding of landscape metrics. Furthermore, landscape connectivity indices sensu Pascual-Hortal and Saura, (2006) and Saura and PascualHortal (2007) are important as a tool for prioritizing habitat patches and landscape elements in conservation decisions and planning. The results of the DPCintra in dPCconnector values for the 15 most important cores are comparable to the results of research on forest habitats (Saura & Rubio, 2010) or even in transnational networks of the protected areas (e.g., Gurrutxaga et al., 2011). Based on an initial assessment of landscape structure (Fig. 2), and with a focus on maintaining connectivity and natural processes in the urban and suburban area of Ljubljana, short dispersal distances were incorporated into our analysis. Despite the construction of highways and urban sprawl over the last decades, the city is still surrounded by connected forest patches, which are identified by large dPCintra and dPCconnector values. The later fraction of the estimated connectivity and availability on the landscape was indicative of limited dispersal distances (Gurrutxaga et al., 2011). Due to the high percentage of forest cover and the favourable distribution of forest patches and cores around the city of Ljubljana, no connection is currently in danger; the weakest link is represented by the G1 and G2 cores stretching from the centre towards the southeast. Another possible critical connection is represented between core areas no. 57, 66 and 81 (Figs. 1b and 3) where proposed Baltic–Adriatic Rail Freight Corridor 5 may hinder existing connections. Therefore the forest in the western part (cores 57, 66, 81) and central part of the analysed area (cores G1 and G2) should not be subject to any kind of clearances in future. With the present model of connectivity and the preservation of natural environments (conservation buffers), it is also possible to determine the starting points of nature preservation strategies. The urban environment of Ljubljana is characterised by a high percentage of forests stretching all the way to the central city. In the central study area, the defining characteristics of forest patches and landscape structure were evaluated according to recommendations: for example, using a watershed scale within the natural environment (Environment Canada, 2013). Although urban and suburban forests cannot be directly compared to watershed forests outside urban areas, the Forest Habitat Guidelines recommend a high share of forest coverage and core forest areas. The 45% of forest cover in the central area is supporting more than half of the potential species richness (Environment Canada, 2013). The city is surrounded by

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Fig. 3. Spatial distribution of the most important forest core areas—nodes (dark grey) and least cost pathway connectivity between them (black). Dashed lines represent the borders of landscape subunits.

Fig. 4. Spatial overview of forests (light grey) and forest loss (black) over a broader study area from 1975 to 2012.

large patches – as many as 23 of them encompass more than 200 ha of the core area (represented by the forest area situated more than 100 m from the forest edge). The largest among them are presented

in Table 2 and in Fig. 3. One of them is even situated within the highway ring road and is connected to the others with a corridor (G1–G2 in Fig. 3) that, due to its width, facilitates species movement. As a

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Fig. 5. Connectivity map with distribution range of annually removed animals from 2006 to 2011, red deer (upper left), wild boar (upper right), roe deer (bottom left) recorded within 1 km square grids (adapted from Jerina, 2012).

result, it is also possible to maintain a portion of natural processes typical of forest landscapes in urban areas. When establishing a spatial connectivity model based on the data on mammals (Fig. 5) it is necessary to consider that kilometresized squares were used as the basis for the analysis on a large spatial scale. The studies of home-range size have shown that the average size of the annual home-range of red deer in Slovenia is 2–3 times larger than a 1 km grid cell (Jerina, 2012). It was shown that transportation routes and their associated disturbances may affect habitat selection of animals as well as their home-range size and shape and that the size of habitat patches between routes limits their home-range size. Roe deer are abundant in the areas of mixed countryside, but their population is also on the increase in suburban and urban areas. Red deer and wild boar have been affected by the highway network and have been avoiding the vicinity of highways; however, the density of both species in study area was satisfying (Jerina, 2012). The cores 4 in 11 (Fig. 3) represent the origins of large densities of deer in the model area. Similar is true for the core 72 and its connections with smaller cores, which enable the wild boar access to the central part of the analysed area (cores G1 and G2). According to a recent analysis of 202 European cities (Kabisch & Haase, 2013), residential urban areas seem to increase regardless of population growth or decline. This is a result of significant increases in the number of households and the number of smaller households demanding larger living spaces. This process of urban expansion is also affecting Ljubljana. The city’s spatial pattern has resulted from Ljubljana’s historic spatial development bound by its topography and the expansion of built up areas alongside important city

inroads that radiate from the centre into other Slovenian regions (Hladnik & Pirnat, 2011). In a comparative analysis of 15 European urban areas, the growth of built-up areas over the last 50 years has taken place mostly on former agricultural land (Kasanko et al., 2006). Despite the fact that most of the land available for urban growth has been agricultural, the same factors were stressed in our analysis in Ljubljana. In most cases, agricultural land was more suitable for construction than forest areas, and natural areas have been protected from urbanisation. In half of the analysed cities, over 90% of all new housing areas were discontinuous or dispersed and have experienced urban sprawl. Urban development that is dispersed in this way can influence the connectivity of forests and natural areas without drastically changing their portion of urban areas. With a decree (Odlok, 2010), the city of Ljubljana declared that forest cover in the central area were Special Purpose Forests. These forests are protected and at the same time characterised by important functions, among which recreation, aesthetics and biodiversity functions are prevailing (Hladnik & Pirnat, 2011), whereas their spatial distribution enables the preservation of connectivity between them; this allows for sustained preservation of their biodiversity. In this way, forests with important connections enable the preservation of biodiversity of so-called inner urban forests and are given a new role, which can be seen as suburban forests surrounding urban forests serving as a cloak and representing an important link between urban and other forests on a broader landscape level. With this article, we would like to draw attention to the numerous possibilities for preserving their connectivity that should be considered in future city planning and development.

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5. Conclusions We have come to the following conclusions and suggestions: 1. Functional landscape connectivity may be enhanced with an indispensable pattern of corridors, stepping stones of natural vegetation and permeable landscape matrix. The methodology adopted in the present study allowed to quantify the contribution of individual forest habitat areas to overall landscape connectivity. A graph representation of a forest habitat mosaic enables an analysis of large study areas and forest patches often required for the conservation purposes at the landscape level (Pascual-Hortal & Saura, 2008) and the assessment of game population dynamics when lacking sufficient data as was the case of Ljubljana. Fragmentation can present a much larger concern than concentrated clearing in only one place along the forest edge. In the case of the G1 and G2 cores (Fig. 3), the clearances resulting from highway construction have already strongly endangered connectivity; therefore, the rest of the forests as well as the extensive surfaces (“forest areas”) should be granted the highest values of biotic function, which would protect them from land use changes. In all other areas where clearing is possible, however, it would be necessary to simulate connectivity changes before the final decision is passed. In this way, spatial connectivity of forest patches would enhance biodiversity in spatial planning. 2. The probability of connectivity (PC) is a habitat availability index obtained by integrating habitat amount (or, in our case, core areas) and connectivity in a single measure (Pascual-Hortal & Saura, 2006; Saura & Pascual-Hortal, 2007). Consequently, PC is both sensitive to different types of changes affecting the landscape mosaic as well as effective in defining crucial landscape elements for the preservation of landscape connectivity from the point of view of habitat availability. To preserve the biotic function of forests and remnants of natural vegetation, the clearings should not extend to the forests with highly preserved close-to-nature structures or inner core areas large enough to enable the preservation of such structures (these are presented by the dPCintra results). If clearings cannot be avoided, it is of vital importance to preserve the forest cores in strategically important areas since they enable connectivity within a landscape or landscape connections between different patches or cores (in our case determined by the dPCconnector values). Finally, the present study suggests that an in-depth evaluation of forest and landscape biodiversity must include the understanding of i. the functional connectivity among forest cores, and ii. the availability of core areas both in time and spatial dimensions. The derived indices are equally important to the ones currently in use (e.g. surface, structure, preservation) as an objectively measured support to decision making in landscape planning and conservation of forested landscapes. Acknowledgements The present article was written in the frame of the 7th Framework Programme Project: Green Infrastructure and Urban Biodiversity for Sustainable Urban Development and the Green Economy (GREEN SURGE). The authors would like thank reviewers for constructive suggestions and amendments. References Bürgi, M., Hersperger, A. M., & Schneeberger, N. (2004). Driving forces of landscape change −current and new directions. Landscape Ecology, 19(8), 857–868. Bentrup, G. (2008). Conservation buffers: design guidelines for buffers, corridors, and greenways. Asheville, NC: Department of Agriculture, Forest Service, Southern Research Station: Gen. Tech. Rep. SRS-109.

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Further reading www.conefor.org. www.dars.si. Dr. Janez Pirnat is Assistant Professor for Landscape Ecology and Urban Forestry, University of Ljubljana, Biotechnical Faculty. His special interests within Landscape Ecology are spatial and temporal changes in the pattern of forest patches, corridors and solitary trees in a cultural landscapes and urban areas as well as non-timber forest functions and ecosystem services. Dr. David Hladnik is Assistant Professor at the University Ljubljana, Biotechnical Faculty, where his research focuses on forest inventories, landscape and forest monitoring.