Next Article in Journal
Temporal and Spatial Evolution of Grey Water Footprint in the Huai River Basin and Its Influencing Factors
Previous Article in Journal
Land Use Conflict Under Different Scenarios Based on the PLUS Model: A Case Study of the Development Pilot Zone in Jilin, China
Previous Article in Special Issue
Red Clay as a Raw Material for Sustainable Masonry Composite Ceramic Blocks
 
 
Search for Articles:
Title / Keyword
Author / Affiliation / Email
Journal
Article Type
 
 
Advanced Search
 
Section
Special Issue
Volume
Issue
Number
Page
 
Journals
Sustainability
Volume 17
Issue 15
10.3390/su17157158
sustainability-logo
Submit to this Journal Review for this Journal Propose a Special Issue
► Article Menu

Article Menu

share Share announcement Help format_quote Cite question_answer Discuss in SciProfiles
first_page
settings
Order Article Reprints
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:
Background:
Article

Evaluating Landscape Fragmentation and Consequent Environmental Impact of Solar Parks Installation in Natura 2000 Protected Areas: The Case of the Thessaly Region, Central Greece

by
Ioannis Faraslis
1,*,
Vassiliki Margaritopoulou
2,
Christos Christakis
1 and
Efthimios Providas
1
1
Department of Environmental Sciences, University of Thessaly, 41500 Larissa, Greece
2
Management Unit of Parnassos and Oiti National Parks and Protected Areas of Eastern Central Greece, Natural Environment and Climate Change Agency, 35002 Amfiklia, Greece
*
Author to whom correspondence should be addressed.
Sustainability 2025, 17(15), 7158; https://doi.org/10.3390/su17157158
Submission received: 28 May 2025 / Revised: 28 July 2025 / Accepted: 1 August 2025 / Published: 7 August 2025
(This article belongs to the Special Issue Environmental Protection and Sustainable Ecological Engineering)
Browse Figures
Versions Notes

Abstract

This study examines the adverse environmental impacts of solar photovoltaic parks located in established protected areas, aiming to determine the level of landscape fragmentation through the calculation of relevant landscape metrics. For this purpose, a case study was carried out in a Mediterranean Natura 2000 Special Protection Area (SPA), and landscape metrics were calculated using Geographic Information System spatial analysis tools. The analysis of metrics showed that the installation of renewable energy parks within the designated protected area negatively affect landscape fragmentation and the absence of carefully defined and evidence-based mitigation measures. The land cover categories that are significantly affected are those considered critical habitats of bird species that have been designated as SPAs. The results of this study highlight the need to integrate, in the National Renewable Energy Spatial Plans, specific biodiversity objectives, such as conservation objectives and the suspension of the installation of photovoltaic parks in certain areas that are important for conservation of biodiversity, in order to ensure the overall sustainability of renewable energy production.

1. Introduction

Biodiversity is undoubtedly essential for the stability of ecosystems and species populations, yet it is declining at a very rapid rate. The main cause is land use changes that lead to habitat fragmentation and loss [1,2,3,4,5,6,7], while drastically affecting ecological processes [8]. Agricultural land occupies more than half of the area of the European Union (EU) and, in addition to providing food security, important natural resource management, and socio-economic rural development, is a vital parameter for supporting wildlife, as approximately 50% of flora and fauna species, including those listed in the annexes of EU directives, depend on agricultural practices [9,10,11,12,13,14]. All the above make the sustainable use of these areas significantly important for the conservation of biodiversity, while, on the other hand, land use changes lead to adverse effects. The total area of Utilized Agricultural Area (UAA) [15] abandoned in recent decades within the EU is particularly high and is expected to increase in the coming years [16]. Abandoned UAA is the main cause of land use changes in EU agroecosystems with direct negative impacts on biodiversity and ecosystem services, such as pollination, food security, jobs, climate maintenance, and carbon storage [1,2,3,7,10,17,18,19,20,21].
According to the latest report from the European Habitats and Birds Directives, only 15% of habitats, 27% of fauna species, and especially 47% of avifauna are in a favorable conservation status [22]. Due to the number of protected species that depend on agricultural ecosystems, it is essential that EU national agricultural policies are consistent with the Biodiversity Conservation Strategy in order to avoid the further degradation of and decline in habitats and populations of these species, while complying with the provisions of EU legislation and directives, such as the 92/43/EEC Directive, the 2009/147/EC (Birds) Directive, the EU 2028/841 Regulation and the Natura Restoration Act [11,14,17,18].
Land use changes due to agricultural land abandonment [10,21] have been intensified by the installation of numerous renewable energy plants [19]. Over the past twenty years, these plants have evolved from an alternative to the main technology replacing fossil fuel energy production, a change driven by the energy crisis and climate change [23]. At the same time, relevant European legislation has been reformed to support this transition [24].
Photovoltaic (solar) power plants constitute the vast majority of renewable energy installations located on agricultural land in Greece, including highly productive agricultural land, such as the Thessaly plain [25], a large part of which is included in the Natura 2000 network of protected areas.
The efficiency of solar energy production depends mainly on the characteristics of the installation location, which makes agricultural land in Greece ideal for this purpose: many hours of sunshine per year, with favorable temperatures and humidity. Considering the low installation costs, the high network connectivity due to the existing rural road network, and the financial incentives given to farmers for land leases, today photovoltaic parks occupy large areas in the Thessaly plain [25].
Although the placement of solar parks on arable land can play a supporting role in biodiversity through specific measures/practices [26], the majority of cases contradict biodiversity conservation objectives and the needs of agricultural production: their placement is decided without taking into account the long-term impacts on the environment, ecosystem services, and/or other socio-economic criteria [27].
Landscape structure determines the ecological characteristics of an area. Therefore, studying whether landscape functions can be affected by landscape structural changes is important in planning and decision-making. Landscape characteristics can be determined both spatially and quantitatively, using Geographic Information Systems (GIS), estimating the magnitude of changes in landscape structure and the effects on their functions and ecological processes [28]. In recent decades, landscape metrics have become a key tool for quantifying landscape changes and spatial ecological structure. Metrics such as patch number, mean patch size, and mosaic can greatly enhance the understanding of the impact of human activities on different land cover types [29,30].
While the interest in installing solar parks in protected areas is particularly high in Greece, it is mainly characterized by a lack of spatial planning in a context of sustainable development. The aim of this article is to investigate the negative impacts of installed solar parks within Natura 2000 areas, on the ecological functions and protected subjects of these areas. To this end, landscape metrics were calculated and analyzed using GIS in a protected area in the region of Thessaly, with an already high percentage of land covered by solar parks and high interest in adding more installations.

2. Materials and Methods

2.1. Case Study Area

The study area is the Special Protection Area (SPA) of the Natura 2000 network “Periochi Thessalikou Kampou” (GR1420011), as shown in Figure 1. It is located within the plain of Thessaly, which has a total area of 1,403,600 hectares, of which 403,045 are cultivated and constitute 10% of the country’s agricultural land—the largest in Greece [25]. The SPA, which covers an area of 95,905.36 hectares, is dominated by cereal and other crop fields, small settlements, water bodies (tributaries of Pinios river and small canals) and scarce thickets. The area is characterized by the existence of small spatial mosaics—an aggregation of distinct heterogenous isolated areas—with natural vegetation, surrounded by the agricultural landscape matrix. These areas, despite being fragmented by human activities, support important ecological processes. The designated species in the SPA of the study are the Lesser kestrel (Falco naumanni) and the Long-legged buzzard (Buteo rufinus), while a plethora of other agricultural species are also protected, mainly passerines of lowland fields, such as the Eurasian Skylark (Alauda arvensis) and the Calandra lark (Melanocorypha calandra), various species of herons (Ardea cinerea, Nycticorax nycticorax, Egretta garzetta, etc.) and a variety of predators (Circus ssp., Falco ssp.).
It is noted that although the area is home to many other species, the conservation target species of this NATURA 2000 site is the Lesser kestrel and the Long-legged buzzard, as these are the species for which the NATURA area was established. The two species are considered farmland birds, which mainly forage in open agricultural areas, with fairly low vegetation.
The Lesser kestrel lives in warm, open habitats such as steppe and pseudo-steppe areas, fallow, non-irrigated farmlands with a preference to cultivated lands with alfa-alfa or cereal, and uncultivated grassland with low vegetation cover. Its diet consists mainly of insects and, to a lesser extent, small mammals and other small vertebrates [31,32]. It has been found that the species has a specialized feeding strategy, as it changes its diet during the nest incubation and chick rearing period, where it feeds on large amounts of Orthoptera, compared to the rest of the breeding season, where it has a more variable diet, consisting mainly of species from both the Orthoptera and the Coleoptera orders [33,34]. The region under study is of great importance for the Lesser kestrel, as it is the main breeding area for almost 70% of the Greek population, 8% of the European and 1.5% of the global population of the species. The landscape mosaic formed by uncultivated zones, cereal crops and water canals constitutes a suitable foraging habitat, while the traditional tiled roofs of the small settlements scattered in the area provide abundant nesting sites for the species [31,35]. The Lesser kestrel, which had suffered a huge decline in its population due to loss and degradation of its habitats (tiled roof restorations and increased use of agrochemicals), continues to be threatened by land use changes, mainly due to the conversion of crop fields to photovoltaic parks and livestock units (intensive and semi-intensive livestock farming), causing loss foraging habitats [31,32,36], thus reducing the overall abundance of arthropods that the species preys upon, which seems to play an important role both during the breeding season and during pre-migration period [33,34].
The Long-legged buzzard is an adaptable species that mainly inhabits open areas. Slightly hilly plains are ideal nesting sites. While Long-legged buzzards predominantly forage in wildlands, they are also adaptable to cultivations, pastures, village outskirts, and sometimes even heavily farmed areas. In Greece, the Long-legged buzzard is a partially migratory species. It inhabits open areas with low hills, scattered rocks, phrygana, sparse maquis, grasslands, extensive farmland, and, locally, sparsely forested pine areas. It nests mainly on cliffs and more rarely in trees. Its diet consists of small to medium-sized mammals, reptiles, birds, and large arthropods [37,38].
The conservation of those species depends on the preservation of open agricultural areas with scarce tree rows, which is also beneficial for other protected species under the E.U. Directives [38,39,40].

2.2. Materials

For the analysis and evaluation of the data, several metrics specific to landscape ecology were calculated using Quantum-GIS, an open-source Geographic Information System, and the LecoS (Landscape ecology Statistics) plugin.
The data collected concern solar parks that are already installed or are under approval for installation within the study area. These spatial data cover the period from 2018 to 2022 and were collected from several public authorities, as shown in Table 1. Data from EU Corine Land Cover (CLC) of the Copernicus program, with a reference year of 2018, were also used to calculate land cover changes based on the location of solar park installations [41]. Finally, the ecological network of protected areas [42] was retrieved by the European Environment Agency datahub (European network of protected sites).
To identify and map the critical habitats of priority species in NATURA 2000 SPA sites, a systematic survey was carried out to record the populations of these species during the breeding, migratory, and wintering periods, through fieldwork lasting 20 to 60 days over two breeding seasons (or at least one, if sufficient reliable data already existed). Data collection was based on point counts, line transects, direct counts, and targeted observations from selected vantage points, depending on the species and the specific characteristics of each area. Throughout the surveys, key breeding, foraging, roosting, and sheltering sites were accurately located and mapped. Habitat mapping also relied on vegetation or habitat-type maps, combined with field observations [43].
Utilizing the LecoS GIS plugin, the following five (5) key landscape metrics were calculated to assess fragmentation and isolation of different land cover categories in the study area [44,45].
Percentage of Landscape (percentage). The ratio of each type of land cover to the total area of the landscape under consideration is
P L A N D = P i = ∑ J = 1 n a i j A 100 ,
where P i is the percentage of the total area covered by land cover type i , α i j is the area in square meters of patch i j , and A is the total area of the landscape in square meters. When a land cover type that constitutes a critical habitat for a species is being reduced it means habitat loss, resulting in negative pressure for that species. Therefore, the comparison of the percentage of landscape for a land cover type before and after the installation of photovoltaic parks is an important indicator of habitat loss.
Percentage Like Adjacencies (percentage). The proportion of adjacent plots having the same land cover type is
P L A D J = g i i ∑ k = 1 m g i k ( 100 ) ,
where g i i is the number of adjacencies between cells of the same class i , and g i k is the total number of adjacencies in the landscape between cells of classes i and k . It is an indicator of landscape connectivity, as higher numbers indicate less fragmentation, which in the present case study would indicate a homogenous landscape of open areas without disturbances that comprise the ideal feeding habitats of the Lesser kestrel and the Long-legged buzzard. Therefore, the comparison of this landscape metric before and after the installation of photovoltaic parks may indicate a potential increase in fragmentation.
Effective Mesh Size (hectares). Quantification of landscape connectivity and matrix permeability, based on cell data, is
M E S H = ∑ J = 1 n a i j 2 A 1 10,000 ,
where α i j is the area in square meters of patch i j , and A is the total area of the landscape in square meters. It is a relative measurement of the structure of each spatial mosaic. It provides an insight into species mobility as well as potential gene flow and therefore assesses the effects of habitat fragmentation on species dispersal/gene flow. A higher number indicates a homogenous landscape of open areas without disturbances that comprise the ideal feeding habitats of the Lesser kestrel and the Long-legged buzzard. Therefore, the comparison of this landscape metric before and after the installation of photovoltaic parks can show probable loss of connectivity and increase in fragmentation.
Total Edge (meters). The total perimeter/length of all boundaries (edges) of for each type of land cover is
T E = ∑ k = 1 m e i k ,
where e i k is the total length of edges (in meters) of class i . A large number indicates boundary density and thus a level of landscape fragmentation, which directly and indirectly affects species and populations. In this study, smaller numbers of total edge are preferred, since they would indicate a more homogenous landscape of open areas without disturbances that comprise the ideal feeding habitats of the Lesser kestrel and the Long-legged buzzard. Therefore, the comparison of this landscape metric before and after the installation of photovoltaic parks can show probable loss of connectivity and increase in fragmentation.
Edge Density (meters per hectare). The density of edges per defined landscape area for each class (land cover category) is
E D = ∑ k = 1 m e i k A ( 10,000 ) ,
where e i k is the total length of edges (in meters) of class i and A is the total area of the landscape in square meters. It is the total perimeter divided by the total area of each class. A large number indicates a density of boundaries and therefore a level of fragmentation/isolation and it can also be considered as a measure of landscape complexity. In the present case study, smaller numbers of edge density are preferred, since they would indicate a more homogenous landscape of open areas without disturbances that comprise the ideal feeding habitats of the Lesser kestrel and the Long-legged buzzard. Therefore, the comparison of this landscape metric before and after the installation of photovoltaic parks can show probable loss of connectivity and increase in fragmentation.

2.3. Methods

Four basic methodology steps were used for investigating the impact of solar park installation and operation on ecological functions due to fragmentation, as shown in Figure 2.

2.3.1. Collection and Analysis of Geospatial Data

Initially, the appropriate data for the study objectives were selected through queries within the original database that had been previously acquired and were trimmed into several relevant files (approved or not for installation, separation of different categories of environmental legislation, point/polygon—vector files). Subsequently, all geospatial data were projected into a common geospatial reference system (Greek Grid—EPSG: 2100). Finally, the vector data describing the locations of the solar parks were converted into raster format (mosaics/raster-GeoTIFF) and merged with the corresponding raster file describing land cover [41].

2.3.2. Creation of Possible Scenarios

Three primary and five secondary scenarios were created, based on different assumptions on current and future solar park placement distribution in the area, in order to assess landscape fragmentation and investigate the impact on the ecological functions and objectives of the Natura 2000 site.
Primary Scenarios:
  • S0: It constitutes the reference scenario, meaning there are no solar park projects in the study area (CLC18 data only)—see Figure 3.
  • S1: The most likely scenario for the distribution of solar parks in the study area, as it includes existing parks and all parks approved for installation—see Figure 4.
  • S2: The over-installation scenario, which represents the installation of solar park projects at all stages of permitting. This includes all projects in scenario S1 along with those with a low probability of installation—see Figure 5.
Secondary Scenarios:
  • SL1: It concerns the installation of solar parks with a capacity of less than 1 MW (considered “small”), for which, under the legislation, the environmental impact assessment process is relatively simple.
  • SG1: It concerns the installation of all solar parks, including those with a capacity less than 1 MW as well as those with a capacity of greater than 1 MW (considered “large”), as in Scenario S2. For the large installations, under the legislation, the environmental impact assessment process includes field work.
  • S0-CH: It concerns only the critical habitats of protected bird species in the SPA in the reference Scenario S0, i.e., excluding all solar parks in the study area (CLC 18 data only)
  • SL1-CH: It concerns only the critical habitats of the protected bird species in the SPA, using the corresponding land cover data and solar park data in the Scenario SL1.
  • SG1-CH: It concerns only the critical habitats of the protected bird species in the SPA, using the corresponding land cover data and solar park data in the Scenario SG1.
It is noted that the scenarios reported separately for the distinct project capacity categories (“small” and “large”) were designed solely with the aim of identifying possible different impacts that these categories may have on land cover and the environment.

2.3.3. Calculation of Landscape Metrics and Comparison of the Different Scenarios

Landscape metrics were calculated for all scenarios using the GIS software plugin LecoS, for the following three land categories, based on the 2018 CLC layer:
  • Seasonal Herbaceous Vegetation (SHV). This is agricultural land with seasonal herbaceous vegetation.
  • Permanent Herbaceous Vegetation (PHV). This category includes all arable land with permanent herbaceous vegetation (including intensive and extensive grasslands). It also includes all vegetation-covered, but non-woody surfaces, including natural grasslands, clear cuts, pastures, parks, lawns in residential gardens, or green areas related to traffic. In the study area, PHV refers to grasslands and pastures with herbaceous vegetation that is permanent but not woody, and it can be found scattered among the seasonal agricultural fields.
  • Sparse or No Vegetation (SNV). According to the EUNIS (European Environment Agency), the SNV type includes miscellaneous bare habitats, with vascular plants absent or very sparse. In the study, it refers to sparse vegetation and unstable areas with stones, boulders, or rubble on steep slopes where the vegetation layer covers between 10% and 50% of the surface, which can be abandoned areas and areas that have bare surfaces (rocks, boulders, bare soil). This type of land can be found in marginal areas of the Thessaly plain.
Initially, the results were compared between the main Scenarios S1 and S2 to identify possible differences in landscape fragmentation and its ecological functions, and the results of both scenarios were compared with Scenario S0 (control) to assess the overall impact of solar park installations on important (in terms of biodiversity conservation) landscapes such as the Natura 2000 SPA site and critical habitats of protected species.
Subsequently, the secondary scenarios involving small and large solar park projects were also compared, both in the Natura 2000 area and in critical habitats of protected species, in order to assess any differences in fragmentation and ecological functions due to the size of installation. Finally, these scenarios were also compared with the secondary control scenario within the same areas.

3. Results

In this section, the results are presented and interpreted to determine the changes in the landscape due to the solar park installations in the different scenarios, and to what extent important features/functions of the protected areas are affected, such as landscape connectivity and the existence of a sufficient number of corridors. At the same time, an assessment of the existing spatial planning for the installation of solar parks is carried out in terms of environmental impacts, as the data included already-installed projects. These results showed to what extent the current spatial planning prepared for the approval procedures for the installation of solar parks contributes to environmental protection and sustainability.

3.1. Landscape Metrics

Landscape metrics were calculated for the main land cover categories of interest in the study area (SPA-GR1420011), i.e., agricultural land or low vegetation areas, where solar parks are usually installed.
In Table 2, Table 3 and Table 4 the landscape metrics for Seasonal Herbaceous Vegetation (SHV), Permanent Herbaceous Vegetation (PHV), and Sparse or No Vegetation (SNV) land categories, respectively, are presented.

3.2. Changes in Land Cover

According to the PLAND metric, the SHV land cover type is 74.5% of the study area, as shown in Table 2. This type of land cover, in Scenario S1 (Figure 4), decreases to 70.3%, while in Scenario S2 (Figure 5), it decreases to 65.6%. The next major land cover category PHV, in Scenario S0 (Figure 3), occupies 16.6% of the SPA, decreasing to 15.1% in Scenario S1 and 13.1% in Scenario S2, as illustrated in Table 3. Finally, regarding the SNV land cover category, no difference is recorded between the two Scenarios S1 and S2. Specifically, from 0.26% in Scenario S0 it decreases to 0.24% in Scenario S1 and Scenario S2, as shown in Table 4.
When comparing Scenario SL1 and Scenario SG1, the percentage of coverage reduction is equal for both small and large solar park installations in all three land cover categories.
Furthermore, within the critical habitats of the protected bird species in the SPA, land cover percentages decreases for all land cover categories in both Scenarios SL1-CH and SG1-CH, compared to the control Scenario S0-CH. Specifically, for the SHV category, the percentage of critical habitat coverage is reduced from 62.3% in Scenario S0-CH to 52.7% in Scenario SG1-CH, as listed in Table 2. Accordingly, for the PHV category, the percentage of critical habitat coverage decreases from 22.1% to 16.8.7%, while for SNV it decreases from 0.324% to 0.247%. Generally, reductions in land cover are expected, as solar parks require large areas of land, thereby changing land cover classes. However, the above recorded rates of reduction in critical habitat cover within the SPA due to the installation of solar farms are considered particularly high and should be of concern.

3.3. Changes in Connectivity

The two-landscape metrics that assess landscape connectivity, namely PLADJ, which indicates landscape connectivity, and MESH, which quantify this connectivity, decrease in all scenarios across all land cover classes, except for Scenario SL1-CH in the SHV and SNV land cover classes (Table 2 and Table 4, respectively). This is attributed to the fact that small solar park installations create more boundaries. In general, however, landscape connectivity decreases as solar park coverage increases.

3.4. Changes in Fragmentation

The landscape fragmentation metrics, TE, which measures the total length of boundaries, and ED, which measures the length of boundaries per area, vary. In the scenarios comparing small and large installations, boundary length was found to be shorter for large installations (>1 MW) in the scenarios involving both the entire study area and the critical habitats. The metrics also indicate high boundary densities for both control scenarios.

4. Discussion

Land use change is the main cause of biodiversity decline due to fragmentation and habitat loss. The trend of accelerating renewable energy installations as part of the green transition to mitigate climate change has not yet been assessed in this context, although phenomenologically it is a factor that further enhances habitat and biodiversity loss [1,2,3,4,5,6,7]. Renewable energy park installations can also be found (and in large numbers) within protected areas, a situation that deserves more attention, given the importance and vulnerability of these areas worldwide [46,47,48]. The need to preserve protected areas, combined with the need for land for renewable energy production, inevitably creates a contradictory situation. In order to achieve balance, proper spatial planning and structured decision-making, taking into account appropriate assessments and leveraging modern tools and analytical data, are crucial. This approach contributes to reducing the negative environmental impacts of renewable energy production and assessing their effectiveness at all levels, ensuring sustainable development for climate change mitigation, while preserving biodiversity.
The use of Geographic Information Systems (GIS) in assessing ecosystem changes is widespread and is considered a reliable way to study areas that have a functional role in biodiversity conservation, while also facilitating the quantification and visualization of data [28,48,49,50,51,52,53]. Similarly, the calculation of basic landscape metrics is considered an indispensable tool in spatial planning and decision-making, as characteristics critical for habitat conservation, such as fragmentation and landscape connectivity, can be quantified and, therefore, interpreted and assessed on a case-by-case basis, taking into account the habitat requirements of the target species [44,54,55,56].
Greece, which has an ambitious renewable energy strategy (supported by incentive legislation along with simplified approval procedures), has made remarkable progress in the transition to green energy, ranking first among all EU countries in relative efficiency compared to the size of its GDP in 2023, as 19% of total electricity production came from solar parks [57]. However, an updated spatial planning framework for renewable energy generation has not yet been legislated, while the existing one (in force since 2008) was approved without an environmental impact assessment [58]. In this context, several scientific studies have been conducted to evaluate and propose potential “environmentally friendly” locations for green energy installations in Greece, but they mainly focus on wind farm installations [59,60,61], while there is a lack of relevant literature on solar parks. Furthermore, publicly available data and services only concern solar parks with a capacity >1 MW, as the respective regulatory platforms have not yet been updated, which is an obstacle to the objective assessment of the overall environmental impacts, given the significant cumulative impact when considering the large number of “small” (<1 MW capacity) solar parks. Furthermore, not all relevant available data are geospatial, and a large proportion is descriptive (only coordinates and areas are available).
In this study, data were collected for the full range of solar park installations and—where necessary—converted into geospatial data in order to calculate landscape metrics for various scenarios within the project area (the Natura 2000 SPA site GR1420011).
The results show that in the Thessaly plain, the installation of solar parks within a protected area without specific planning aimed at preserving the habitats of protected species can lead to a major change in land cover categories, to the detriment of these habitats and consequently biodiversity in general. In all scenarios examined by the study, it is concluded that the installation of solar parks leads to a reduction in land types of interest within the protected area, including critical habitats of protected species. Natura 2000 sites consist of critical habitats of protected species, ecological corridors, and protected habitat types, and the maintenance of these features is important at a local, national, and European level, as they are fundamental elements for the ecological coherence of the network, which is the basis of its designation [62].
In the study area, the Natura 2000 SPA site “Periochi Thessalikou Kampou”, land use change leads to loss of foraging habitats of the two important species of the area (the Lesser kestrel and the Long-legged buzzard), as the species selects foraging habitats depending on the characteristics of the areas (permanent, periodic, low, or no vegetation). During the process of solar park, new roads, small buildings, solar panel housing, and solar panels are constructed, completely changing the characteristics of the area. Furthermore, vegetation is extirpated (in worst-case scenarios by agrochemicals), which leads to habitat loss and indirectly affecting the species that utilize an area. In general, habitat loss increases the chances of species displacement and intra- and/or inter-species competition, and while edge length is expanding, the “edge effect” is increasing and access of predators is greater, leading to food chain imbalances.
In addition to the habitat loss for key species observed in all scenarios considered, an effort was made to assess fragmentation and connectivity levels using relevant landscape metrics. Connectivity decreased in most scenarios, indicating fragmentation, except for two cases where smaller capacity (<1 MW) and therefore smaller size solar parks were assessed. In these cases, the Effective Mesh Size (MESH) metric showed higher values. This metric quantifies the probability that two randomly selected pixels within an area are connected to a common fundamental area—(matrix) [54,63]. Therefore, additional data are required for safe interpretation, as the matrix may incorporate the area of the solar parks. Overall, increased fragmentation leads to habitat isolation, limiting species movements and preventing genetic exchange between individuals. Over time, this reduces population size and genetic diversity, ultimately leading to biodiversity loss.
The landscape metrics for edge length and density, which generally correlate with fragmentation [44,56], showed an overall increase with solar park installation—except in the case pf parks with capacity >1 MW (“large” solar parks). While this may seem contradictory given the greater land occupation of larger parks, it can be explained by the fact that numerous small installations create more boundaries than fewer, larger ones. However, the results also indicate relatively high boundary densities for the control scenarios, suggesting that additional data are needed for a more comprehensive understanding.
Although further research is needed to fully understand how the installation and siting of parks affects ecological functions and the population of protected species in designated areas, some points can be highlighted. Larger solar parks (>1 MW), despite occupying extensive areas, are predominantly composed of a single significant area versus numerous smaller, dispersed areas, as is the case for <1 MW facilities. This is a key point, as mitigation measures for larger facilities can be more easily implemented and monitored. In contrast, many smaller parks may pose greater challenges, as the cost and complexity of implementing and monitoring mitigation measures could be disproportionately high in relation to their size and capacity.
Given these considerations, the design and placement of solar parks should account for protected species, including their critical habitats (breeding and foraging), distances from nesting sites, and other ecological factors, in order to avoid negative impacts on the species populations. Additionally, solar park installation within a given area should be evaluated comprehensively through the procedure of appropriate assessment to determine whether cumulative barriers to movement and dispersal are created, hinder nesting, or obstruct foraging of the protected species. A GIS can provide spatial insights regarding these evaluations and can therefore be used as a tool for the visualization, processing, and analysis of multiple spatial datasets. These insights are essential for spatial planning, including the designation of exclusion zones and the identification of optimal “biodiversity friendly” installation locations, highlighting the importance of GIS-based decision-making.
This study provides the basis for an initial local-level landscape metric analysis for solar park installation. For a more comprehensive evaluation aimed at sustainable spatial installation planning at a national level, the analysis should include data relating to the ecology, biology, and habitat preferences of each protected area species, and more specialized metrics or/and methods should be applied, such as species presence/absence modeling.
While solar park installations within protected areas should generally be avoided [7,48,58,64,65], there are cases where appropriate mitigation measures can minimize impacts. Furthermore, utilizing thorough spatial planning, and the application of targeted mitigation actions, new installations in areas already facing ecological problems, like extensive areas with monocultures, can partially contribute to habitat restoration [26,48,51,62,66,67,68,69,70]. Additionally, in other cases, renewable energy park installations can also serve as a land management tool. Land abandonment has been a growing issue in recent years, often leading to loss of open areas in forests which are crucial for biodiversity conservation. Renewable energy parks installed under a specific for the area management regime can help maintain these open areas and contribute to biodiversity conservation [71,72].
Several mitigation measures that have been recently implemented solar and wind power parks, though relatively new, have already proven effective in reducing habitat fragmentation and species displacement and some have even shown to support biodiversity, such as agrivoltaics, panel placing on roads and rooftops, creation of artificial species hideouts places within the park area, special avoidance markings on panels, and adjusting panel spacing [71,73,74,75,76,77,78]. Additionally, the use of GISs is considered a prerequisite for the effective evaluation of the impact of solar parks on a case-by-case basis, both before the installation and through ongoing monitoring during the parks’ operation [26,47,79,80,81,82].
Nevertheless, direct effects of photovoltaic installations on animal mortality, species distribution, or habitat connectivity remain poorly studied. While the behavior of arthropods has been relatively well explored, there is still a significant knowledge gap concerning higher trophic levels, particularly bird populations [70]. Furthermore, ecological concerns and land use conflicts arise, as photovoltaic installations compete with other land uses—such as agriculture, forestry, conservation, and urban development—potentially leading to trade-offs between objectives like food security, biodiversity conservation, and local economic opportunities. As such, strategic site selection and integrated land use planning are crucial to reducing negative impacts and fostering beneficial outcomes [83]. However, in some cases solar parks can enhance biodiversity: they have been shown to support greater bird species richness and diversity, particularly among invertebrate-feeding species, likely due to the increased structural complexity found in solar park environments [81], concerning the Black Redstart, European Stonechat, White Wagtail, and Eurasian Tree Sparrow as indicator species for these habitats but not raptor species, as discussed in this study.
As land is required for both mitigating climate change and for halting biodiversity loss, a coordinated strategy is necessary, aiming at global and local considerations [48,84,85,86]. In order to achieve sustainability, the implementation of green technologies must ensure that biodiversity, agricultural, and natural landscapes are conserved. In this context, assessing the environmental impact of green energy installations is crucial, and an integration within National Renewable Energy Spatial Plans including specific biodiversity goals will ensure the overall sustainability of green energy production.
In conclusion, the results of this study indicate that “small” parks increase landscape fragmentation, and “large” solar parks disrupt landscape connectivity, indicating the increase in target species habitat loss when more solar parks are installed. Yet, the relationship between habitat loss and species populations is not linear, especially concerning bird populations that are highly mobile, indicating that the line between what is measurable or mappable and what holds ecological significance for the process being studied or managed is not clearly defined [87]. For this reason, addressing the direct effects of solar parks’ installation on the target species populations is not possible in the context of this study. Nevertheless, this study provides critical insights into this complicated interdependence, presenting the effects of Solar Park installation on relevant landscape features. Moreover, it should be noted that this study has certain limitations. The 10 m resolution raster analysis of the Corine Land Cover (CLC) 2018 data could lead to potential underestimation of fragmentation effects that can be found in higher resolution data. Moreover, as solar parks in all available data are given as the total area of the field occupied, by not distinguishing specific characteristics such as panel spacing and free area in the park, the calculated metrics and findings of this study can only be attributed to distribution and size of solar parks, not accounting for panel spacing, infrastructure design, etc., that can potentially provide valuable insights. This data, however, is not currently available.

5. Conclusions

The rapid expansion of renewable energy production facilities within the framework of the green transition concept has not been adequately assessed in terms of its impact on protected areas. Natura 2000 Special Protection Areas consist of critical habitats for key species, ecological corridors, and important habitat types whose conservation is essential for biodiversity conservation both locally and in a global sense. The installation of photovoltaic parks within these areas without effective spatial planning and other related measures could significantly reduce the habitats of protected species, as observed in this study, which may lead to a conflict between biodiversity conservation and green energy development. In the study area, a Special Protection Area of the Thessaly plain in central Greece, the calculation of relevant landscape metrics revealed that connectivity showed a decrease in all the scenarios evaluated, except for the cases of small solar parks (<1 MW capacity solar parks). Furthermore, edge metrics indicated increased fragmentation, which poses a serious threat to ecosystem structure and functions. Moreover, data analysis showed that solar park installations could significantly reduce the habitats of key protected species, with estimates indicating losses up to 10%. The reduction in available foraging habitat increases the likelihood of species displacement, disrupts ecological balance, and negatively affects genetic flow within populations. To mitigate these impacts, modern tools such as Geographic Information Systems and metric landscape analysis can provide accurate and reliable data for informed decision-making. Identifying threats to biodiversity is a critical step in minimizing the ecological impacts of solar park installations. While these energy generation facilities should generally be avoided within protected areas, certain mitigation measures can help reduce their impact and support biodiversity, while facilitating sustainable energy development.

Author Contributions

Conceptualization, I.F., V.M. and C.C.; methodology, I.F. and C.C.; software, I.F.; data curation, V.M.; writing—original draft preparation, I.F., V.M. and C.C.; writing—review and editing, I.F., C.C. and E.P. All authors have read and agreed to the published version of the manuscript.

Funding

This research received no external funding.

Institutional Review Board Statement

Not applicable.

Informed Consent Statement

Not applicable.

Data Availability Statement

The original contributions presented in this study are included in the article. Further inquiries can be directed to the corresponding author.

Acknowledgments

The authors would like to thank the anonymous reviewers for their valuable suggestions and comments.

Conflicts of Interest

The authors declare no conflicts of interest.

Abbreviations

The following abbreviations are used in this manuscript:
EUEuropean Union
SPASpecial Protection Area
UAAUtilized Agricultural Area
GISGeographic Information System
LecoSLandscape ecology Statistics

References

  1. Hasan, S.S.; Zhen, L.; Miah, M.G.; Ahamed, T.; Samie, A. Impact of land use change on ecosystem services: A review. Environ. Dev. 2020, 34, 100527. [Google Scholar] [CrossRef]
  2. Davison, C.W.; Rahbek, C.; Morueta-Holme, N. Land-use change and biodiversity: Challenges for assembling evidence on the greatest threat to nature. Glob. Change Biol. 2021, 27, 5414–5429. [Google Scholar] [CrossRef]
  3. Allan, J.R.; Possingham, H.P.; Atkinson, S.C.; Waldron, A.; Di Marco, M.; Butchart, S.H.M.; Adams, V.M.; Kissling, W.D.; Worsdell, T.; Sandbrook, C.; et al. The minimum land area requiring conservation attention to safeguard biodiversity. Science 2022, 376, 1094–1101. [Google Scholar] [CrossRef]
  4. Caro, T.; Rowe, Z.; Berger, J.; Wholey, P.; Dobson, A. An inconvenient misconception: Climate change is not the principal driver of biodiversity loss. Conserv. Lett. 2022, 15, e12868. [Google Scholar] [CrossRef]
  5. Jaureguiberry, P.; Titeux, N.; Wiemers, M.; Bowler, D.E.; Coscieme, L.; Golden, A.S.; Guerra, C.A.; Jacob, U.; Takahashi, Y.; Settele, J.; et al. The direct drivers of recent global anthropogenic biodiversity loss. Sci. Adv. 2022, 8, eabm9982. [Google Scholar] [CrossRef]
  6. Isbell, F.; Balvanera, P.; Mori, A.S.; He, J.; Bullock, J.M.; Regmi, G.R.; Seabloom, E.W.; Ferrier, S.; Sala, O.E.; Guerrero-Ramírez, N.R.; et al. Expert perspectives on global biodiversity loss and its drivers and impacts on people. Front. Ecol. Environ. 2023, 21, 94–103. [Google Scholar] [CrossRef]
  7. Kati, V.; Kassara, C.; Panagos, P.; Tampouratzi, L.; Gotsis, D.; Tzortzakaki, O.; Petridou, M.; Psaralexi, M.; Sidiropoulos, L.; Vasilakis, D.; et al. The overlooked threat of land take from wind energy infrastructures: Quantification, drivers and policy gaps. J. Environ. Manag. 2023, 348, 119340. [Google Scholar] [CrossRef] [PubMed]
  8. McWilliams, C.; Lurgi, M.; Montoya, J.M.; Sauve, A.; Montoya, D. The stability of multitrophic communities under habitat loss. Nat. Commun. 2019, 10, 2322. [Google Scholar] [CrossRef] [PubMed]
  9. Brambilla, M.; Guidali, F.; Begri, I. The importance of an agricultural mosaic for Cirl Buntings Emberiza cirlus in Italy. Ibis 2008, 150, 628–632. [Google Scholar] [CrossRef]
  10. Terres, J.-M.; Scacchiafichi, L.N.; Wania, A.; Ambar, M.; Anguiano, E.; Buckwell, A.; Coppola, A.; Gocht, A.; Källström, H.N.; Pointereau, P.; et al. Farmland abandonment in Europe: Identification of drivers and indicators, and development of a composite indicator of risk. Land Use Policy 2015, 49, 20–34. [Google Scholar] [CrossRef]
  11. Bengtsson, J.; Bullock, J.M.; Egoh, B.; Everson, C.; Everson, T.; O’Connor, T.; O’Farrell, P.J.; Smith, H.G.; Lindborg, R. Grasslands—more important for ecosystem services than you might think. Ecosphere 2019, 10, e02582. [Google Scholar] [CrossRef]
  12. Moran, J.; Byrne, D.; Carlier, B.; Finn, J.A.; Uallachain, D.; Sullivan, C.A. Management of high nature value farmland in the Republic of Ireland: 25 years evolving toward locally adapted results-orientated solutions and payments. Ecol. Soc. 2021, 26, 20. [Google Scholar] [CrossRef]
  13. Voudouri, A.; Chaideftou, E.; Sfougaris, A. Topsoil seed bank as feeding ground for farmland birds: A comparative assessment in agricultural habitats. Land 2021, 10, 967. [Google Scholar] [CrossRef]
  14. Alblas, E.; van Zeben, J. ‘Farming out’ biodiversity: Implementing EU nature law through agri-environmental schemes. Earth Syst. Gov. 2023, 17, 100180. [Google Scholar] [CrossRef]
  15. Eurostat Statistics Explained. Glossary: Utilised Agricultural Area (UAA). Available online: https://ec.europa.eu/eurostat/statistics-explained/index.php?title=Glossary:Utilised_agricultural_area_(UAA) (accessed on 5 October 2024).
  16. Perpiñá Castillo, C.; Kavalov, B.; Diogo, V.; Jacobs-Crisioni, C.; Batista e Silva, F.; Lavalle, C. Agricultural Land Abandonment in the EU Within 2015–2030; European Commission: Brussels, Belgium, 2018. [Google Scholar]
  17. Zakkak, S.; Chatzaki, M.; Karamalis, N.; Kati, V. Spiders in the context of agricultural land abandonment in Greek Mountains: Species responses, community structure and the need to preserve traditional agricultural landscapes. J. Insect Conserv. 2014, 18, 599–611. [Google Scholar] [CrossRef]
  18. Zakkak, S.; Radovic, A.; Nikolov, S.C.; Shumka, S.; Kakalis, L.; Kati, V. Assessing the effect of agricultural land abandonment on bird communities in southern-eastern Europe. J. Environ. Manag. 2015, 164, 171–179. [Google Scholar] [CrossRef] [PubMed]
  19. Nunez-Regueiro, M.; Siddiqui, S.E.; Fletcher, R.J., Jr. Effects of bioenergy on biodiversity arising from land-use change and crop type. Conserv. Biol. 2019, 35, 77–87. [Google Scholar] [CrossRef]
  20. Szangolies, L.; Rohwander, M.S.; Jeltsch, F. Single large AND several small habitat patches: A community perspective on their importance for biodiversity. Basic Appl. Ecol. 2022, 65, 16–27. [Google Scholar] [CrossRef]
  21. Chontos, K.; Tsiripidis, I. Open Habitats under Threat in Mountainous, Mediterranean Landscapes: Land Abandonment Consequences in the Vegetation Cover of the Thessalian Part of Mt Agrafa (Central Greece). Land 2023, 12, 846. [Google Scholar] [CrossRef]
  22. European Environment Agency. State of Nature in the EU—Results from Reporting Under the Nature Directives 2013–2018; EEA Report No 10/2020; Publications Office of the European Union: Luxembourg, 2020; Available online: https://www.eea.europa.eu/en/analysis/publications/state-of-nature-in-the-eu-2020 (accessed on 20 August 2024).
  23. REN21. Renewables 2023 Global Status Report Collection: Global Overview; REN21 Secretariat: Paris, France, 2023; Available online: https://www.ren21.net/gsr-2023/ (accessed on 15 September 2024).
  24. European Commission. The Wildlife Sensitivity Mapping Manual: Practical Guidance for Renewable Energy Planning in the European Union; Publications Office of the European Union: Luxembourg, 2020; Available online: https://op.europa.eu/en/publication-detail/-/publication/a3f185b8-0c30-11eb-bc07-01aa75ed71a1/language-en (accessed on 10 April 2024).
  25. Sargentis, G.-F.; Siamparina, P.; Sakki, G.-K.; Efstratiadis, A.; Chiotinis, M.; Koutsoyiannis, D. Agricultural Land or Photovoltaic Parks? The Water–Energy–Food Nexus and Land Development Perspectives in the Thessaly Plain, Greece. Sustainability 2021, 13, 8935. [Google Scholar] [CrossRef]
  26. Tinsley, E.; Froidevaux, J.S.P.; Zsebok, S.; Szabadi, K.L.; Jones, G. Renewable Energies and Biodiversity: Impact of Ground-Mounted Solar Photovoltaic Sites on Bat Activity. J. Appl. Ecol. 2023, 60, 1752–1762. [Google Scholar] [CrossRef]
  27. Kirk-Hall, P.; Whitney, W.; Richardson, J. Land Use Conflicts Between Wind and Solar Renewable Energy and Agriculture Uses. Law Fac. Scholarsh. 2022, 104, 21. Available online: https://researchrepository.wvu.edu/cgi/viewcontent.cgi?article=1104&context=law_faculty (accessed on 10 May 2024).
  28. Das, S.; Adhikary, P.P.; Kumar, P.; Bera, B. Urban Wetland Fragmentation and Ecosystem Service Assessment Using Integrated Machine Learning Algorithm and Spatial Landscape Analysis. Geocarto Int. 2021, 37, 7800–7818. [Google Scholar] [CrossRef]
  29. Zatelli, P.; Gobbi, S.; Tattoni, C.; Cantiani, M.G.; La Porta, N.; Rocchini, D.; Zorzi, N.; Ciolli, M. Relevance of the Cell Neighborhood Size in Landscape Metrics Evaluation and Free or Open Source Software Implementations. ISPRS Int. J. Geo-Inf. 2019, 8, 586. [Google Scholar] [CrossRef]
  30. Murunga, K.W.; Nyadawa, M.; Sang, J.; Cheruiyot, C. Characterizing Landscape Fragmentation of Koitobos River Sub-Basin, Trans-Nzoia, Kenya. Heliyon 2024, 10, e29237. [Google Scholar] [CrossRef] [PubMed]
  31. Christakis, C.E.; Sfougaris, A.I. Foraging Habitat Selection by the Lesser Kestrel Falco naumanni During the Different Phases of Breeding and the Post Breeding Period in Central Greece. Ornithol. Sci. 2021, 20, 175–183. [Google Scholar] [CrossRef]
  32. Bounas, A. Falco naumanni. The Red List of Greece. Available online: https://redlist.necca.gov.gr/en/assessment/?id=224415641 (accessed on 20 October 2024).
  33. Bounas, A.; Sotiropoulos, K. Change of Feeding Strategy Prior to Migration: A Comparative Diet Analysis in the Lesser Kestrel (Falco naumanni). Avian Biol. Res. 2017, 10, 27–35. [Google Scholar] [CrossRef]
  34. Christakis, C.; Makri, M.; Alivizatos, H.; Sfougaris, A. Lesser Kestrel Falco naumanni Diet During Different Phases of Breeding and Post Breeding Periods in Central Greece. Avocetta 2023, 47, 1–17. [Google Scholar] [CrossRef]
  35. Portolou, D.; Bourdakis, S.; Vlachos, C.; Kastritis, T.; Dimalexis, T. (Eds.) Important Bird Areas of Greece: Priority Sites for Conservation; Hellenic Ornithological Society: Athens, Greece, 2009. (In Greek) [Google Scholar]
  36. Aparicio, J.M.; Muñoz, A.; Cordero, P.J.; Bonal, R. Causes of the Recent Decline of a Lesser Kestrel (Falco naumanni) Population Under an Enhanced Conservation Scenario. Ibis 2022, 165, 388–402. [Google Scholar] [CrossRef]
  37. Friedemann, G.; Yom-Tov, Y.; Motro, U.; Leshem, Y. Shift in Nesting Ground of the Long-Legged Buzzard (Buteo rufinus) in Judea, Israel—An Effect of Habitat Change. Biol. Conserv. 2011, 144, 402–406. [Google Scholar] [CrossRef]
  38. Demedzhiev, D.; Dobrev, V.; Popgeorgiev, G. Effects of Habitat Change on Territory Occupancy, Breeding Density and Breeding Success of Long-Legged Buzzard (Buteo rufinus Cretzschmar, 1827) in Besaparski Ridove Special Protection Area (Natura 2000), Southern Bulgaria. Acta Zool. Bulg. 2014, 5, 191–200. [Google Scholar]
  39. Baltag, E.S.; Pocora, V.; Bolboaca, L.E.; Ion, C. The Importance of Low-Intensive Agricultural Landscape for Birds of Prey. Land 2021, 10, 252. [Google Scholar] [CrossRef]
  40. Demedzhiev, D. Breeding Parameters and Factors Influencing the Reproduction of an Expanding Long-Legged Buzzard (Buteo rufinus) Population Under High Breeding Density Conditions. J. Ornithol. 2022, 163, 405–415. [Google Scholar] [CrossRef]
  41. CLCplus Backbone 2018 (Raster 10 m), Europe, 3-Yearly. European Union’s Copernicus Land Monitoring Service Information. Available online: https://sdi.eea.europa.eu/catalogue/copernicus/api/records/cd534ebf-f553-42f0-9ac1-62c1dc36d32c?language=all (accessed on 12 December 2023).
  42. Natura 2000. European Network of Protected Sites. Available online: https://sdi.eea.europa.eu/catalogue/srv/api/records/0801ff11-24ae-4c6b-852f-029965df5bc5?language=all (accessed on 15 August 2024).
  43. Hadjicharalambous, H.; Dimalexis, A.; Bourdakis, S.; Bouzbouras, D. Definition of Methodology and Specification Drafting for the Evaluation of Areas and Their Designation as Special Protection Areas for Birds, with Pilot Implementation in 10 Areas: Volume of Analytical Specifications; Hellenic Ministry for the Environment, Physical Planning and Public Works, Athens and Greek Biotope/Wetland Centre (EKBY): Thermi, Greece, 2004. Available online: https://ypen.gov.gr/wp-content/uploads/legacy/Files/Perivallon/Diaxeirisi%20Fysikoy%20Perivallontos/Ektheseis%20-%20Meletes/20200326_ornithologiki_aksiologisi_GR056.pdf (accessed on 19 June 2025). (In Greek)
  44. McGarigal, K.S.; Cushman, S.; Maile, N.; Ene, E. FRAGSTATS: Spatial Pattern Analysis Program for Categorical Maps. Available online: https://www.researchgate.net/publication/259011515_FRAGSTATS_Spatial_pattern_analysis_program_for_categorical_maps (accessed on 12 February 2024).
  45. Turner, M.G.; Gardner, R.H. Landscape Ecology in Theory: Pattern and Process, 2nd ed.; Springer: New York, NY, USA, 2015. [Google Scholar]
  46. Rehbein, J.A.; Watson, J.E.M.; Lane, J.L.; Sonter, L.J.; Venter, O.; Atkinson, S.C.; Allan, J.R. Renewable energy development threatens many globally important biodiversity areas. Glob. Change Biol. 2020, 26, 3040–3051. [Google Scholar] [CrossRef]
  47. Beinnun, L.; van Bochove, J.; Ng, C.; Fletcher, C.; Wilson, D.; Phair, N.; Carbone, G. Mitigating Biodiversity Impacts Associated with Solar and Wind Energy Development. Guidelines for Project Developers; IUCN: Gland, Switzerland; The Biodiversity Consultancy: Cambridge, UK, 2021. [Google Scholar]
  48. Kim, J.Y.; Koide, D.; Ishihama, F.; Kadoya, T.; Nishihiro, J. Current site planning of medium to large solar power systems accelerates the loss of the remaining semi-natural and agricultural habitats. Sci. Total Environ. 2021, 779, 146475. [Google Scholar] [CrossRef]
  49. Trisurat, Y.; Shrestha, R.P.; Alkemade, R. Land Use, Climate Change and Biodiversity Modelling: Perspectives and Applications; IGI Global: Hershey, PA, USA, 2011. [Google Scholar]
  50. Jung, M.; Leco, S. A python plugin for automated landscape ecology analysis. Ecol. Inform. 2016, 31, 18–21. [Google Scholar] [CrossRef]
  51. Thomas, K.A.; Jarchow, C.J.; Arundel, T.R.; Jamwal, P.; Borens, A.; Drost, C.A. Landscape-scale wildlife species richness metrics to inform wind and solar energy facility siting: An Arizona case study. Energy Policy 2018, 116, 145–152. [Google Scholar] [CrossRef]
  52. Klein, J.; Haverkamp, P.J.; Lindberg, E.; Griesser, M.; Eggers, S. Remotely sensed forest understory density and nest predator occurrence interact to predict suitable breeding habitat and the occurrence of a resident boreal bird species. Ecol. Evol. 2020, 10, 2238–2252. [Google Scholar] [CrossRef]
  53. Yang, X.; Mu, Y.; Yang, L.; Yu, Y.; Wu, Z. Impacts of climate change on forest biodiversity changes in Northeast China. Remote Sens. 2024, 16, 4058. [Google Scholar] [CrossRef]
  54. Schmiedel, I.; Bergmeir, E.; Culmsee, H. Plant species richness patterns along a gradient of landscape modification intensity in Lower Saxony, Germany. Landsc. Urban Plan. 2015, 141, 41–51. [Google Scholar] [CrossRef]
  55. Wei, X.; Xiao, X.; Li, Q.; Li, P.; Xiang, C. Evaluating the effectiveness of landscape configuration metrics from landscape composition metrics. Landsc. Ecol. Eng. 2017, 13, 169–181. [Google Scholar] [CrossRef]
  56. Fahrig, L. Effects of habitat fragmentation on biodiversity. Annu. Rev. Ecol. Evol. Syst. 2003, 34, 487–515. [Google Scholar] [CrossRef]
  57. Ernst & Young Global Limited (EY). Renewable Energy Country Attractiveness Index (RECAI) 2023, 61st ed.; Ernst & Young: London, UK, 2023. [Google Scholar]
  58. European Commission. Reasoned Opinion Art. 258 NATURE—Failure to Comply with Habitats Directive When Planning Windfarm Projects in Greece (Case Number INFR(2014)4073). Available online: https://ec.europa.eu/atwork/applying-eu-law/infringements-proceedings/infringement_decisions/?lang_code=en (accessed on 10 May 2024).
  59. Dimalexis, A.; Kastritis, T.; Manolopoulos, A.; Korbeti, M.; Fric, J.; Saravia Mullin, V.; Xirouchakis, S.; Bousbouras, D. Identification and Mapping of Sensitive Bird Areas to Wind Farm Development in Greece; Hellenic Ornithological Society: Athens, Greece, 2010; p. 126. [Google Scholar]
  60. WWF. Wind Farms in Thrace: Updating the Proposal for Proper Site Selection; WWF: Dadia, Athens, Greece, 2013. Available online: https://tethys.pnnl.gov/sites/default/files/publications/WWF-windfarms-Thrace.pdf (accessed on 15 May 2024).
  61. Kati, V.; Kassara, C.; Vrontisi, Z.; Moustakas, A. The biodiversity–wind energy–land use nexus in a global biodiversity hotspot. Sci. Total Environ. 2021, 768, 144471. [Google Scholar] [CrossRef]
  62. Gaston, K.J.; Jackson, S.F.; Nagy, A.; Cantu-Salazar, L.; Johnson, M. Protected areas in Europe: Principle & Practice. Ann. N. Y. Acad. Sci. 2008, 1134, 97–119. [Google Scholar] [CrossRef]
  63. Hasa, E.; Hysa, A.; Teqja, Z. Quantifying landscape fragmentation via effective mesh size landscape metric: Case of Albania. Agric. For. 2021, 67, 215–230. [Google Scholar] [CrossRef]
  64. Harrison, C.; Lloyd, H.; Field, C. Evidence Review of the Impact of Solar Farms on Birds, Bats and General Ecology, 1st ed.; Natural England: York, UK; Manchester Metropolitan University: Manchester, UK, 2017. [Google Scholar]
  65. Watson, J.E.M.; Venegas-Li, R.; Grantham, H.; Dudley, N.; Stolton, S.; Rao, M.; Woodley, S.; Hockings, M.; Burkart, K.; Simmonds, J.S.; et al. Priorities for protected area expansion so nations can meet their Kunming-Montreal Global Biodiversity Framework commitments. Integr. Conserv. 2023, 2, 1–16. [Google Scholar] [CrossRef]
  66. Hochkirch, A.; Schmitt, T.; Beninde, J.; Hiery, M.; Kinitz, T.; Kirschey, J.; Matenaar, D.; Rohde, K.; Stoefen, A.; Wagner, N.; et al. Europe Needs a New Vision for a Natura 2000 Network. Conserv. Lett. 2012, 6, 462–467. [Google Scholar] [CrossRef]
  67. Cooper, D.S. Industrial-scale solar projects and birds in the California desert: Assessing impacts and developing mitigation. In Proceedings of the Sonoran Joint Venture, Tucson, AZ, USA, 10 November 2016. [Google Scholar]
  68. Taylor, R.; Conway, J.; Gabb, O.; Gillespie, J. Potential Ecological Impacts of Ground-Mounted Photovoltaic Solar Panels; BSG Ecology: Newport, UK, 2019. [Google Scholar]
  69. Rahman, A.; Farrok, O.; Haque, M.M. Environmental impact of renewable energy source based electrical power plants: Solar, wind, hydroelectric, biomass, geothermal, tidal, ocean, and osmotic. Renew. Sustain. Energy Rev. 2022, 161, 112279. [Google Scholar] [CrossRef]
  70. Lafitte, A.; Sordello, R.; Ouedraogo, D.Y.; Thiery, C.; Marx, G.; Froidevaux, J.; Schatz, C.; Kerbiriou, C.; Gourdain, P.; Reyjol, Y. Existing evidence on the effects of photovoltaic panels on biodiversity: A systematic map with critical appraisal of study validity. Environ. Evid. 2023, 12, 25. [Google Scholar] [CrossRef] [PubMed]
  71. Peschel, R.; Peschel, T.; Marchand, M.; Hauke, J. Solar Parks—Profits for Biodiversity; Association of Energy Market Innovators (bne/Bundesverband Neue Energiewirtschaft e.V.): Berlin, Germany, 2019. [Google Scholar]
  72. Sathaye, J.; Lucon, O.; Rahman, A.; Christensen, J.; Denton, F.; Fujino, J.; Heath, G.; Mirya, M.; Rudnick, H.; Schlaepfer, A.; et al. Renewable Energy in the Context of Sustainable Development. In IPCC Special Report on Renewable Energy Sources and Climate Change Mitigation; Edenhofer, O., Pichs-Madruga, R., Sokona, Y., Seyboth, K., Matschoss, P., Kadner, S., Zwickel, P., Eickemeier, G., Hansen, G., Eds.; Cambridge University Press: Cambridge, UK; New York, NY, USA, 2011. [Google Scholar]
  73. Hernandez, R.R.; Easter, S.B.; Murphy-Mariscal, M.L.; Maestre, F.T.; Tavassoli, M.; Allen, E.B.; Barrows, C.W.; Belnap, J.; Ochoa-Hueso, R.; Ravi, S.; et al. Environmental impacts of utility-scale solar energy. Renew. Sustain. Energy Rev. 2014, 29, 766–779. [Google Scholar] [CrossRef]
  74. Dinesh, H.; Pearce, J.M. The potential of agrivoltaic systems. Renew. Sustain. Energy Rev. 2016, 54, 299–308. [Google Scholar] [CrossRef]
  75. Ravi, S.; Macknick, J.; Lobell, D.; Field, C.; Ganesan, K.; Jain, R.; Elchinger, M.; Stoltenberg, B. Colocation opportunities for large solar infrastructures and agriculture in drylands. Appl. Energy 2016, 165, 383–392. [Google Scholar] [CrossRef]
  76. Handler, R.; Pearce, J.M. Greener sheep: Life cycle analysis of integrated sheep agrivoltaic systems. Cleaner Energy Syst. 2022, 3, 100036. [Google Scholar] [CrossRef]
  77. Xia, Z.; Li, Y.; Zhang, W.; Chen, R.; Guo, S.; Zhang, P.; Du, P. Solar photovoltaic program helps turn deserts green in China: Evidence from satellite monitoring. J. Environ. Manag. 2022, 324, 116338. [Google Scholar] [CrossRef]
  78. Endiz, M.S. Agrivoltaic Systems: Combining Food and Energy Production. In Proceedings of the International Conference on Engineering Technologies (ICENTE’23), Konya, Turkey, 23–25 November 2023. [Google Scholar]
  79. Montag, H.; Parker, G.; Clarkson, T. The Effects of Solar Farms on Local Biodiversity: A Comparative Study; Clarkson and Woods: Blackford, UK; Wychwood Biodiversity: Kingsbridge, UK, 2016. [Google Scholar]
  80. Blaydes, H.; Potts, S.G.; Whyatt, J.D.; Armstrong, A. Opportunities to enhance pollinator biodiversity in solar parks. Renew. Sustain. Energy Rev. 2021, 145, 111065. [Google Scholar] [CrossRef]
  81. Jarčuška, B.; Gálffyová, M.; Schnürmacher, R.; Baláž, M.; Mišík, M.; Repel, M.; Fulín, M.; Kerestúr, D.; Lackovičová, Z.; Mojžiš, M.; et al. Solar parks can enhance bird diversity in agricultural landscape. J. Environ. Manag. 2024, 351, 119902. [Google Scholar] [CrossRef]
  82. Zanden, H.B.V.; Nelson, D.M.; Conkling, T.J.; Allison, T.D.; Diffendorfer, J.E.; Dietsch, T.V.; Fesnock, A.L.; Loss, S.R.; Ortiz, P.A.; Paulman, R.; et al. The geographic extent of bird populations affected by renewable-energy development. Conserv. Biol. 2024, 38, e14191. [Google Scholar] [CrossRef]
  83. Bošnjakovic, M.; Santa, R.; Crnac, Z.; Bošnjaković, T. Environmental Impact of PV Power Systems. Sustainability 2023, 15, 11888. [Google Scholar] [CrossRef]
  84. Beatty, B.; Macknick, J.; McCall, J.; Braus, G. Native Vegetation Performance Under a Solar PV Array at the National Wind Technology Center; David Buckner ESCO Associates Inc.: Skokie, IL, USA; National Renewable Energy Laboratory (NREL): Golden, CO, USA, 2017. Available online: www.nrel.gov/publications (accessed on 5 February 2024).
  85. Gasparatos, A.; Doll, C.N.H.; Esteban, M.; Ahmed, A.; Olang, T.A. Renewable energy and biodiversity: Implications for transitioning to a Green Economy. Renew. Sustain. Energy Rev. 2017, 70, 161–184. [Google Scholar] [CrossRef]
  86. Smallwood, K.S. Utility-scale solar impacts to volant wildlife. J. Wildl. Manag. 2022, 86, e22216. [Google Scholar] [CrossRef]
  87. Gustafson, E. Quantifying Landscape Spatial Pattern: What Is the State of the Art? Ecosystems 1998, 1, 143–156. [Google Scholar] [CrossRef]
Sustainability 17 07158 g001
Figure 1. The study area, Natura 2000 Special Protection Area “Periochi Thessalikou Kampou” (GR1420011) in the Thessaly plain.
Figure 1. The study area, Natura 2000 Special Protection Area “Periochi Thessalikou Kampou” (GR1420011) in the Thessaly plain.
Sustainability 17 07158 g001
Sustainability 17 07158 g002
Figure 2. The four basic methodology steps of the study.
Figure 2. The four basic methodology steps of the study.
Sustainability 17 07158 g002
Sustainability 17 07158 g003
Figure 3. Land cover map according to Corine 2018 for the SPA GR1420011—“Scenario S0”.
Figure 3. Land cover map according to Corine 2018 for the SPA GR1420011—“Scenario S0”.
Sustainability 17 07158 g003
Sustainability 17 07158 g004
Figure 4. Land cover map according to Corine 2018 for the SPA GR1420011—“Scenario S1”.
Figure 4. Land cover map according to Corine 2018 for the SPA GR1420011—“Scenario S1”.
Sustainability 17 07158 g004
Sustainability 17 07158 g005
Figure 5. Land cover map according to Corine 2018 for the SPA GR1420011—"Scenario S2”.
Figure 5. Land cover map according to Corine 2018 for the SPA GR1420011—"Scenario S2”.
Sustainability 17 07158 g005
Table 1. Geospatial data used in the study—sources and data types.
Table 1. Geospatial data used in the study—sources and data types.
DataSourceData TypeDate of Access
CLC + Backbone 2018 Europe, 3-yearlyCopernicus Land Monitoring ServiceRaster—10 mDecember 2023
Natura 2000 areas European network of protected sites (Natura 2000)VectorJuly 2022
Critical avifauna habitatsGreek Ministry of Environment and Energy (https://ypen.gov.gr/perivallon/viopoikilotita/diktyo-natura-2000/ (accessed on 20 July 2022))VectorJuly 2022
Solar parks with Producer Certificate (Power > 1 MW)Greek Regulatory Authority for Waste, Energy & Water (RAAEY) (https://geo.rae.gr/ (accessed on 10 April 2024))VectorApril 2024
Solar parks with Installation Permit (Power > 1 MW)Greek Regulatory Authority for Waste, Energy & Water (RAAEY) Vector—Shapefile (shp.)April 2024
Solar parks with Operating License (Power > 1 MW)Greek Regulatory Authority for Waste, Energy & Water (RAAEY) (https://geo.rae.gr/ (accessed on 10 April 2024))Vector—Shapefile (shp.)April 2024
Solar parks (Power < 1 MW) Management Unit of Protected Areas of Thessaly—Natural Environment & Climate Change Agency. (https://www.thessaly.gov.gr/organotikidomi/ypiresia?gd_id=10&dnsi_id=2 (accessed on 5 May 2024))Descriptive data (centrobaric coordinates of installation fields, areas of installation land, park power capacity, etc.)May 2024
Table 2. Quantified landscape metrics for all scenarios concerning SHV (Seasonal Herbaceous Vegetation) Corine land cover category.
Table 2. Quantified landscape metrics for all scenarios concerning SHV (Seasonal Herbaceous Vegetation) Corine land cover category.
ScenarioMetric
Composition MetricsConnectivity
Metrics		Fragmentation
Metrics
PLANDPLADJMESHTEED
S074.48388.545,667.1723,497,10036.47
S170.29687.344,293.9593,660,90039.79
S265.63887.534,140.6973,368,90036.47
SL169.87387.644,668.7383,538,00038.84
SG164.70187.533,349.1163,319,60036.13
S0-CH62.29071.7115.5631,098,00082.27
SL1-CH56.42272.4122.039963,90082.23
SG1-CH52.73572.1113.046913,90076.95
Table 3. Quantified landscape metrics for all scenarios concerning PHV (Permanent Herbaceous Vegetation) Corine land cover category.
Table 3. Quantified landscape metrics for all scenarios concerning PHV (Permanent Herbaceous Vegetation) Corine land cover category.
ScenarioMetric
Composition MetricsConnectivity
Metrics		Fragmentation
Metrics
PLANDPLADJMESHTEED
S016.55851.4184.2884,073,20042.47
S115.05351.716.0803,675,20039.94
S213.10348.250.8633,509,70038.00
SL114.99252.1113.5643,617,90039.72
SG112.63948.045.1933,406,60037.08
S0-CH22.07340.65.683996,80074.68
SL1-CH18.10742.04.861789,40067.34
SG1-CH16.82840.24.229766,40064.53
Table 4. Quantified landscape metrics for all scenarios concerning SNV (Sparse or No Vegetation) Corine land cover category.
Table 4. Quantified landscape metrics for all scenarios concerning SNV (Sparse or No Vegetation) Corine land cover category.
ScenarioMetric
Composition MetricsConnectivity
Metrics		Fragmentation
Metrics
PLANDPLADJMESHTEED
S00.26128.4 0.027111,8001.17
S10.23624.80.021108,9001.18
S20.24226.30.018108,5001.17
SL10.24827.30.025108,5001.19
SG10.21024.70.01797,4001.06
S0-CH0.32425.40.02320,6001.54
SL1-CH0.30526.40.02619,0001.62
SG1-CH0.24719.50.00917,8001.50
Disclaimer/Publisher’s Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content.

Share and Cite

MDPI and ACS Style

Faraslis, I.; Margaritopoulou, V.; Christakis, C.; Providas, E. Evaluating Landscape Fragmentation and Consequent Environmental Impact of Solar Parks Installation in Natura 2000 Protected Areas: The Case of the Thessaly Region, Central Greece. Sustainability 2025, 17, 7158. https://doi.org/10.3390/su17157158

AMA Style

Faraslis I, Margaritopoulou V, Christakis C, Providas E. Evaluating Landscape Fragmentation and Consequent Environmental Impact of Solar Parks Installation in Natura 2000 Protected Areas: The Case of the Thessaly Region, Central Greece. Sustainability. 2025; 17(15):7158. https://doi.org/10.3390/su17157158

Chicago/Turabian Style

Faraslis, Ioannis, Vassiliki Margaritopoulou, Christos Christakis, and Efthimios Providas. 2025. "Evaluating Landscape Fragmentation and Consequent Environmental Impact of Solar Parks Installation in Natura 2000 Protected Areas: The Case of the Thessaly Region, Central Greece" Sustainability 17, no. 15: 7158. https://doi.org/10.3390/su17157158

APA Style

Faraslis, I., Margaritopoulou, V., Christakis, C., & Providas, E. (2025). Evaluating Landscape Fragmentation and Consequent Environmental Impact of Solar Parks Installation in Natura 2000 Protected Areas: The Case of the Thessaly Region, Central Greece. Sustainability, 17(15), 7158. https://doi.org/10.3390/su17157158

Note that from the first issue of 2016, this journal uses article numbers instead of page numbers. See further details here.

Article Metrics

Back to TopTop