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Ecological Indicators 129 (2021) 108024
Available online 26 July 2021
1470-160X/© 2021 The Author(s). Published by Elsevier Ltd. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).
Proposal of new Natura 2000 network boundaries in Spain based on the
value of importance for biodiversity and connectivity analysis for
its improvement
Víctor Rinc´
on
a
, Javier Vel´
azquez
b
,
c
,
*
, Javier Guti´
errez
b
, Ana Hernando
b
,
c
,
Alexander Khoroshev
d
, Inmaculada G´
omez
b
, Fernando Herr´
aez
b
, Beatriz S´
anchez
b
,
Juan Pablo Luque
b
, Antonio García-abril
c
, Tom´
as Santamaría
b
, Daniel S´
anchez-Mata
a
a
Departamento de Farmacología, Farmacognosia y Bot´
anica, Facultad de Farmacia, Universidad, Complutense de Madrid, Plaza de Ram´
on y Cajal, s/n, 28040 Madrid,
Spain
b
Universidad Cat´
olica de ´
Avila, Calle de los Canteros s/n, 05005 ´
Avila, Spain
c
Silvanet Research Group, Universidad Polit´
ecnica de Madrid, Ciudad Universitaria s/n, 28040 Madrid, Spain
d
Faculty of Geography, Lomonosov Moscow State University, Moscow 119991, Russia
ARTICLE INFO
Keywords:
Connectivity
MSPA
PC Index
Natura 2000
Conservation
ABSTRACT
The aim of the Natura 2000 Network is to ensure the conservation of habitats and species in their natural areas of
distribution. Connectivity is an essential part of this conservation. For this purpose, a value map of importance
for biodiversity (V.I.B) was generated proposing 4 levels of protection and overlapped with the Natura 2000
network. New boundaries for the zoning are proposed adding 1.600.000 ha. Two connectivity indices (MSPA and
PC) are calculated in the 4 different scenarios. With these indices it is possible to know the number of existing
nuclei and connectors in each of the scenarios. New boundaries cover more areas of interest for biodiversity as
well as zones of great importance in relation to connectivity. We propose a uniform method that can be
extrapolated to any European territory.
1. Introduction
Biological diversity means the “variability among living organisms of
all kinds, including terrestrial and aquatic (marine and inland water)
organisms, and the ecological complexes of which they are part; it in-
cludes diversity within species, between species and of ecosystems“
(Council of the European Communities, 1992). This is the denition that
was adopted by the 150 nations that signed the Convention on Biological
Diversity at the United Nations Conference on Environment and
Development (UNCED). According to the Rio Convention, the objective
of biodiversity conservation is “the sustainable use of its components
and the fair and equitable sharing of the benets arising out of the uti-
lization of genetic resources, including appropriate access to such re-
sources and the appropriate transfer of relevant technologies,
considering all rights over those resources and technologies” (Council of
the European Communities, 1992).
Europe is home to a unique natural diversity, with areas of high
biodiversity globally recognized and protected under various protection
gures. In addition, many of its species are threatened in Europe (Eu-
ropean Environment Agency, 2005). Protected areas are essential for
biodiversity conservation (Dudley, 2008). In this sense, proposals have
been developed to combat the loss of biodiversity since the middle of the
20th century at national, European and international level (Vel´
azquez,
2008). Systematic conservation planning is necessary to ensure the long-
term maintenance of biodiversity (Groves et al, 2009).
One of the largest internationally coordinated actions of vital
importance for biodiversity conservation is the Natura 2000 Network of
protected areas in the European Union (EU). The main objective of this
approach is to guarantee the persistence of the most valuable species and
habitats in a long term perspective. These species and habitats are
covered by the Birds Directive (Council of the European Communities,
2009), and the Habitats Directive (Council of the European Commu-
nities, 1992).
Therefore, the Natura 2000 Network is based on the Birds Directive
* Corresponding author.
E-mail addresses: virincon@ucm.es (V. Rinc´
on), javier.velazquez@ucavila.es (J. Vel´
azquez), ana.hernando@ucavila.es (A. Hernando), fernando.herraez@ucavila.
es (F. Herr´
aez), beatriz.sanchez@ucavila.es (B. S´
anchez), tomas.santamaria@ucavila.es (T. Santamaría), dsmata@ucm.es (D. S´
anchez-Mata).
Contents lists available at ScienceDirect
Ecological Indicators
journal homepage: www.elsevier.com/locate/ecolind
https://doi.org/10.1016/j.ecolind.2021.108024
Received 20 January 2021; Received in revised form 20 July 2021; Accepted 22 July 2021
Ecological Indicators 129 (2021) 108024
2
(2009/147/EC), which declares the Special Protection Areas for Birds
(SPAs), and the Habitats Directive 92/43/EEC, which will dene the
Special Conservation Areas (SCAs) and thus allows protecting habitats,
ora and fauna of community interest. Important are the sites of com-
munity interest (SCIs), which will be understood as SACs when the
appropriate management measures are applied to them, either through a
Natural Resources Management Plan or a Master Plan for Use and
Management. The member states are responsible for selecting the areas
of community interest that will form part of the Network, as well as
applying a conservation measure to them. Currently, the Natura 2000
Network contains more than 27,000 sites covering 18% of the land in the
European Union (European Commission, 2016). The Habitats Directive
already raises the importance of conserving or, where appropriate,
improving the connectivity of the Natura 2000 Network. In Spain, there
are 118 areas listed in Annex I and 263 species listed in Annex II to the
Habitats Directive. On the other hand, there are 125 species listed in
Annex I of the Birds Directive. All these species are present throughout
the land and marine waters of Spain (Ministerio para la Transici´
on
Ecol´
ogica, 2019). The Natura 2000 Network in Spain currently com-
prises 1467 sites of Community importance (SCIs), which are included in
the lists of SCIs approved by the European Commission, and 644 Special
Protection Areas for Birds (SPAs) which cover a total surface of
approximately 210,000 km
2
. Out of the total extension of the Natura
2000 Network in Spain, more than 137,000 km
2
represent the land area,
which corresponds to about 27% of the Spanish territory, and about
72,500 km
2
to the sea surface (Ministerio para la Transici´
on Ecol´
ogica,
2019).
To achieve the conservation objectives of the Natura 2000 Network,
a good selection of important sites for biodiversity is necessary. This can
be achieved by using values of importance for biodiversity (V.I.B.),
through which the different conservation criteria such as habitats, pro-
tected species or land uses, are related. Based on this V.I.B., the best
areas for the extension of the Natura 2000 Network will be selected,
which would improve connectivity between these areas.
Many connectivity studies have been carried out in recent years, as a
crucial part of biodiversity conservation planning (Hodgson et al., 2016;
Olds et al., 2011). The systematic evaluation of conservation to improve
connectivity should be highlighted in this regard (Correa et al., 2016;
Beger et al., 2010; Bottrill and Pressey, 2012; Vel´
azquez et al., 2017;
Tian et al., 2017), and the fact that there is no legislation that establishes
a better way to preserve natural areas as well as the lack of parameters
and methods to select other new areas. Connectivity plays a transcen-
dental role in the interactions between species and landscapes and is
therefore a fundamental element in the structure of the landscape. The
21st century prototype of connectivity conservation is being pursued
(Crooks and Sanjayan, 2006; Worboys et al., 2010) through hundreds of
habitat network initiatives around the world (Bennett and Mulongoy,
2006). The Natura 2000 Network is created to provide connectivity to
the natural spaces that compose it.
Ecological connectivity can be dened as the ability of a territory to
facilitate to a greater or lesser extent the movements of species and
ecological ows between habitat tesserae (Taylor et al., 1993). Con-
nectivity makes genetic variability among different populations
possible, as well as increasing not only the capacity to recover from any
type of disturbance, but it will also enhance the guarantees of survival of
populations against possible local extinctions (Saura et al., 2011).
Ecological connectivity is currently affected and reduced by several
processes, basically anthropogenic alterations such as changes in land
use (agriculture, urbanization, construction of road infrastructures, etc.)
(Gurrutxaga and Lozano, 2010). This type of alterations in the territory
reduce the continuous surface of vegetation, and increase isolated areas,
and therefore disconnected. This is known as habitat fragmentation
(Forman, 1995). Such isolated zones that arise due to fragmentation
may be like each other or have very different characteristics because of
their new sizes, shapes, boundaries, etc. (Forman, 1995). For this reason,
the existence of connectivity between the different natural spaces is
important (Ministerio para la Transici´
on Ecol´
ogica, 2019). Ecological
connectivity requires continuity and coherence of the landscape; in this
sense, ecological corridors acquire high importance, since they act as
connectors of signicant regions for the conservation of biodiversity that
decrease the negative effects derived from habitats fragmentation
(García and Abad, 2014). Corridors work by linking two or more areas
with similar environmental characteristics. In this way, they secure the
conservation of ecological diversity and biological evolutionary pro-
cesses through the migration and dispersal of species (Bennett and
Mulongoy, 2006). In addition, the intensity of ecological ows is greater
than in the rest of the territory (Simberloff, 1992).
These reasons show the need to conserve and restore protected
natural spaces by improving the connectivity of the territory, given that
it is a fundamental element for the survival of species (De la Fuente et al.,
2018). Ecological connectivity is the most effective if it ensures preser-
vation of zonal-specic communities that favour aboriginal species. At
the same time, one should take into account that corridors may accel-
erate dissemination of invasive species as well which could become
critical in highly transformed areas. Hence, measures to monitor and
control, if possible, alterations in species composition of corridors are
needed in some cases. Though the importance of ecological connectivity
for animal migration is well-known, a planner should not ignore mul-
tifunctionality of corridors both in desirable and undesirable senses. On
the one hand, high connectivity of zonal-specic communities in most
cases ensures control over runoff formation, erosion, natural hazards
(mudows, landslides, extensive oods, etc.), and local climate. On the
other hand, continuity of uniform land cover may result in rapid un-
desirable expansion of natural and/or anthropogenic disturbances. For
example, in some xerophytic forest communities, management activity
is aimed at articial fragmentation of forest cover to prevent expansion
of re events. The challenge for connectivity studies is how to harmonize
the needs to enhance natural ecological ows and to avoid detrimental
effects resulting from disturbances. The objectives of the Natura 2000
Network can only be achieved through the optimal location of the areas
to be protected; in fact, the establishment of nature reserves is a
fundamental pillar of regional conservation strategies (Myers et al.,
2000; Maiorano et al., 2007; Kingsland, 2002), since the establishment
of biological reserves in habitats is a tool for combating biodiversity loss
(Batisse, 1982; Chazdon et al., 2009). The provision of information as
well as criteria to identify conservation priorities is the main objective of
the ecological assessment (Roberts et al., 2003). Therefore, in order to
select protected sites, it is absolutely necessary to dene specic criteria
for the conservation of biological diversity (Geneletti and Van Duren,
2008). In this sense, the optimal selection of sites to be protected is the
foundation on which the decision-making process for nature conserva-
tion should be based (Hernando et al., 2010; Teeffelen and Atte, 2008).
Some methods have been applied at the national and international levels
to identify protected areas that act as nature reserves where the repre-
sentation of diversity is maximized (Pressey et al., 1996; Margules and
Pressey, 2000; Xu et al., 2017; Cantú et al., 2014; Gaston et al., 2006).
For all these reasons, Member States must acquire clear criteria whereby
it is possible to identify and dene protected areas at the European level
in order to improve conservation and nature protection (F¨
orster and
Kleinschmit, 2006).
The purpose of this work is to determine whether the areas included
in the Natura 2000 Network proposed by the Autonomous Communities
(Andalucía and Castilla y Le´
on) have been correctly assigned and
delimited considering their environmental values. The proposal of these
new Natura 2000 network boundaries will allow us to evaluate the
current ecological connectivity capacity of the habitats of the study area.
2. Material and methods
2.1. Study area
The study area focuses on the two largest regions/autonomous
V. Rinc´
on et al.
Ecological Indicators 129 (2021) 108024
3
communities in Spain: Andalucía, which has a total area of 87.599 km
2
and Castilla y Le´
on, which has a total area of 94.224 km
2
(Fig. 1).
Natura 2000 Network in Andalucía covers a total extension of 2.67
million hectares. Of this total, 2,59 million hectares are terrestrial and
only 0,07 million are marine areas. In this way, are distinguished 63
Special Protection Areas (SPA), 190 Sites of Community Interest (SCI)
and 163 Special Conservation Areas (SCA).
The Natura 2000 Network in Castilla y Le´
on is made up of 70 SPAs,
with a total surface area of 1.997.977 ha, and 120 SCAs, with a surface
area of 1.890.600 ha, representing 21,20% and 20,06% of the region
respectively, taking into account the overlap between different areas,
the total surface area of the Network in Castile and Leon is 2.461.759 ha,
occupying 26,13% of Castilla y Le´
on (Fig. 2).
2.2. Methodology
The proposed methodology for the analysis of biodiversity in
Andalucía and Castilla y Le´
on, as well as for the assessment of connec-
tivity of Natura 2000 areas, presents four different phases (Vel´
azquez
et al., 2017; Rinc´
on et al., 2019):
•First phase (Cartographic database): The aim of this phase is to
carry out an inventory, where relevant information for the analysis of
the biological diversity of the protected zones will be collected. The
selection criteria to be considered will also be established at this
stage.
•Second phase (Analysis and assessment of important areas for
biodiversity conservation): A multi-criteria analysis is carried out
to obtain a map of the of Value of Importance for Biodiversity (V.I.B.)
in Andalucía and Castilla y Le´
on. Once the V.I.B. in the study area has
been calculated, a map will display the different values of impor-
tance for biodiversity.
•Third phase (Study of the layout of the Natura 2000 network and
zoning proposal in Andalucía and Castilla y Le´
on): Generation of
scenarios for a proposal of zoning for Natura 2000 conservation. In
this way, a new zoning proposal is obtained for 4 different scenarios,
which has considered the V.I.B., the different land uses (CORINE
Land Cover 2012 by Copernicus) and the areas currently included in
the Natura 2000 Network.
•Fourth phase (Analysis of connectivity at different levels of
biodiversity importance): Connectivity analysis for the different
zoning scenarios of Natura 2000 sites in Andalucía and Castilla y
Le´
on is obtained. On the one hand, structural connectivity Morpho-
logical Spatial Pattern Analysis (MSPA) (Attorre et al., 2007) will be
analysed, it measures the number of connecting elements present as
cores or ecological corridors in the study area. On the other hand, the
second index that we applied is the Probability of Connectivity (PC)
(Attorre et al., 2007). This index measures the importance of each of
the connecting elements previously analysed by means of structural
connectivity.
The following gure (Fig. 3) shows an outline of the phases to be
followed in the methodology.
2.2.1. Phase I. Cartographic database
The factors selected for this work are the percentage of amphibians,
birds, mammals, sh, reptiles and total fauna; species included in N.C.E.
S.; species included in Habitats Directive and Birds Directive; percentage
of protected habitats and Shannon Biodiversity index (Shannon and
Weaver, 1949).
Cartographic information for each factor has been taken from reli-
able databases of the following public administration websites. These
sources are:
•Habitats Directive Protected areas.
•Habitats Directive Protected species.
•Birds Directive Protected Species.
•Corine Land Cover (CLC) 2012.
•National Biodiversity Inventory (NBI): NBI consists in a grid of 10
×10 km. In each cell of the grid, the different species of mammals,
reptiles, sh, birds and amphibians are counted. These data are very
relevant to determine the species richness in the study area, ac-
cording to the existence of species in the grid.
•National Catalogue of Endangered Species (NCES): NCES includes
the taxa or populations of the threatened biodiversity. In the cata-
logue there are categories that the species are confronted with:
critically endangered, endangered species and vulnerable species.
At this stage, the evaluation and selection of the main criteria to
identify the most suitable location for the areas that require protection
under Natura 2000, according to their biodiversity value, was also
addressed. From the information collected, the indicators whereby it is
possible to evaluate the biodiversity of a site have been used to dene
the criteria (Rinc´
on et al., 2019).
2.2.2. Phase II. Analysis and assessment of important areas for biodiversity
conservation
The main objective of the second phase is to carry out an analysis and
to process of the information. This is carrying out and processing in-
formation through a multi – criteria analysis and based on the results we
will obtain a map of the Value of Importance for Biodiversity (V.I.B.).
Therefore, multi-criteria analysis aims to establish a V.I.B. that functions
as a valid criterion and can be considered for decision making in
biodiversity conservation.
To achieve this goal, each criterion (Table 1) was rst evaluated by a
group of 5 experts (academic experts in connectivity, biodiversity
management experts, members of the public administration and others
stakeholders) establishing a weight ranging from (1–5). It is understood
that value 1 is the least important for biodiversity, with 5 being the most
important. The experts were selected according to their experience in
research, biodiversity management and conservation and organizations
for the preservation of biodiversity (Rinc´
on et al., 2019).
Multicriteria analysis is used through Multi-Attribute Utility Theory
(Attorre et al., 2007). The scores for each criterion are summed (Lott,
1926). This method is considered one of the best designed systems in the
world (Eraslan, 2013). The scoring method has three characteristics: the
use of rating factors, the factors are graded on a numerical scale and the
weights reect the importance of each factor (Milkovich et al., 2014).
Fig. 1. Study area. Regions of Andalucía and Castilla y Le´
on in Spain.
V. Rinc´
on et al.
Ecological Indicators 129 (2021) 108024
4
Fig. 2. Natura 2000 Network distribution in Castilla y Le´
on and Andalucía.
Fig. 3. Methodology for the analysis of connectivity of Natura 2000 areas.
Table 1
Pixel 1 Structural connectivity data in Andalucía.
Activity Structural connectivity (MSPA): Pixel 1
Natura 2000 Network Level 1 Level 2 Level 3 Level 4
Study area
(%)
Andalucía
(%)
Study area
(%)
Andalucía
(%)
Study area
(%)
Andalucía
(%)
Study area
(%)
Andalucía
(%)
Study area
(%)
Andalucía
(%)
Cores 97.67 15.72 97.37 30.99 97.04 19.51 97.09 18.57 97.38 17.62
Islets 0.13 0.02 0.10 0.03 0.10 0.02 0.10 0.02 0.11 0.02
Perforations 0.05 0.01 0.09 0.03 0.18 0.04 0.27 0.05 0.30 0.05
Edges 1.87 0.30 2.16 0.69 2.46 0.49 2.31 0.44 1.98 0.36
Loops 0 0 0.01 0 0.01 0 0.01 0 0.01 0
Bridges 0.09 0.01 0.09 0.03 0.07 0.01 0.07 0.01 0.08 0.01
Branches 0.18 0.03 0.18 0.06 0.14 0.03 0.15 0.03 0.15 0.03
V. Rinc´
on et al.
Ecological Indicators 129 (2021) 108024
5
From these scores, a parts per unit of the total is calculated. This method
is used to evaluate various solutions taking into account selected
criteria. The following equation is used for this purpose:
VIB :p1u1(xi1) + p2u2(xi2) + ⋯+pnun(xin)
Where:
pn=weights
un=Subjectiveutilities
xin =Actionsunderanalysis
The table in appendix A.1 shows the description and the different
weights obtained for each criterion.
Taking into account the obtained weights, they are applied to the
different values of each criterion that each 10x10 km grid has. By doing
the summation, the V.I.B. for each grid is obtained and thus the V.I.B.
map can be created, achieving one of the objectives of this work: the
creation of a map showing the areas with the most important biodi-
versity values, according to the Natura 2000 framework.
The generated map of Value of Importance for Biodiversity (V.I.B.) is
obtained by means of the resulted values from phase II. This step was
achieved by interpolation of V.I.B. for the 10 ×10 km grid of the Na-
tional Biodiversity Inventory.
Each grid is assigned a value (V.I.B.). In order to perform the inter-
polation, the centroid of each grid is calculated and the V.I.B. value is
assigned to it. Once the values in points are available, the interpolation
is done. An important feature of the method is that it has a low range of
error compared to other methods. Specically, this range of error is R
2
=7,1688. In addition, this method uses statistical models that give us
the possibility of obtaining prediction models, standard errors of pre-
diction, probabilities (Rinc´
on et al, 2019).
Once the interpolation method has been set up, a map of value of
importance for biodiversity (V.I.B.) is generated, this one is linked to the
map of the Natura 2000 Network sites in Andalucía and Castilla y Le´
on.
2.3. Phase III. Study of the layout of the Natura 2000 network and zoning
proposal in Andalucía and Castilla y Le´
on
Within this third phase, the main objective is to obtain the different
scenarios (different zoning levels to calculate connectivity) in the study
area. For this purpose, a combination of the V.I.B. and the land uses
(CORINE) is carried out for the zoning we were selecting among 4 levels
(level 1, level 2, level 3 and level 4) being level 1 the most restrictive.
Land use in each zone was expected to be well-adapted to landscape
conditions, need for nature protection and enhancing connectivity.
The areas that obtained higher values of V.I.B. were combined with
the current land uses (CLC 2012) to dene the new zoning of the Natura
2000 Network.
Urban-industrial covers were eliminated in this process because they
are not important for biodiversity conservation.
In each of the land use zones, it was possible to classify the distri-
bution of the V.I.B. according to the V.I.B. quartiles. If the V.I.B. value
belonged to the rst quartile (i.e. 25% of the highest values) the highest
level on protection was recommended for a polygon. The value within
the lower quartile required the least strict protection measures or no
such measures. A classication of these polygons into 4 levels of pro-
tection was made according to both the ideal land uses for such con-
servation and the criteria for biodiversity conservation.
Protection levels were then identied (Table A2), they were grouped
depending on the type of protection and the given level by various land
use classications. Considering the level of protection, the zones can be
grouped according to the characteristics of importance for biodiversity
in the study area (Rinc´
on et al., 2019).
In this way, a new zoning proposal was obtained for 4 different
scenarios, which has considered the value of importance for biodiversity
(V.I.B.), the different types of land uses, (CLC 2012), and the zones
currently included in the Natura 2000 Network.
2.3.1. Phase IV. Analysis of connectivity at different levels of biodiversity
importance
After executing the previous phases, we are about to execute the
connectivity analysis (structural connectivity analysis).
The maps and values derived from the previous phase serve as input
for connectivity analysis which has been developed through the Guidos
software (Vogt, 2016; Vogt and Riitters, 2017), analyzing connectivity
among the different scenarios generated from the Value of Importance
for Biodiversity (V.I.B.).
The Morphological Spatial Pattern Analysis (MSPA) is based on a
mathematical analysis of morphological patterns and can classify the
main core habitats, connectors and isolated areas of a given territory
(Hernando et al, 2010). Thanks to this categorization, spatial patterns at
pixel level can be shown on a map, making very sensitive variations over
time (Saura and Pascual-Hortal, 2007). In this case, we will carry out the
analysis with three different pixel sizes, so that comparative results can
be obtained between the different edge sizes (Pixel 1, Pixel 2 and Pixel 3
in MSPA program). The preparation of these maps have been introduced
in the program Guidos, which is responsible for development of con-
nectivity in the study areas. To this end, the maps of differing levels of
biodiversity are introduced in “.tiff” format.
As mentioned above, there are 4 different levels of maps and there-
fore, 15 maps will be produced, one for the analysis of the Natura 2000
Network, and another for the connectivity of each of the levels in 3
different pixels. Pixel 1, where the cores predominate over the connec-
tors, and as the number of pixels increases, the surface of the cores de-
creases and the size of the ecological corridors increases. In this way, we
have pixel 2, which is an intermediate level, and pixel 3, which obtains
the highest corridor surface area values.
A reclassication of the map value is then established:
•Foreground: The value in the foreground indicates the areas pro-
tected or to be protected at the different levels.
•Background: The study areas that are outside the foreground.
When running the analysis of each pixel input to the program,
included as an area of interest, each pixel is assigned to an MSPA class. In
this way, the input foreground image will have an identical surface to
the output image with class assignment (Vogt, 2016).
The MSPA classes dened are as follows (Saura and Rubio, 2010):
•Core: Represents the inner surface of habitats that is not altered by
the edge effect.
•Islet: These are habitats that are isolated and, due to their limited
size, cannot form a core.
•Bridge: These are connectors that establish a relationship between
one core and another. They are recognized as effective corridors.
•Branch: Linear connector of pixels that joins a bridge, loop, perfo-
ration or edge at each end.
•Loop: Narrow surface of pixels connecting a single core within a
hole.
•Perforation: Perimeter surrounding an area of background within a
core.
•Edge: Perimeter of pixels that includes each core unit.
Analysis of the connectivity importance (PC):
The PC (Probability of Connectivity) index makes it possible to assess
functional connectivity based on habitat availability, dispersal proba-
bilities and graph structures (Soille and Vogt, 2009). As shown by Saura
and Rubio (2010) the dPC importance values for each landscape element
can be divided into three fractions that quantify the different ways in
which that landscape can contribute to habitat connectivity and
availability:
V. Rinc´
on et al.
Ecological Indicators 129 (2021) 108024
6
dPC =dPCintra +dPCflux +dPCconnector
where dPC is the amount of area connected (intrapatch connectivity),
dPcCintra is Available habitat area provided by patch, dPCux is the
potential amount of dispersal ow expected to exit or reach a habitat
patch, dPCconnector is the extent to which a particular landscape
element acts as a connecting or stepping stone between other forest
habitat areas (by cores and bridges) (Saura et al., 2011).
Vel´
azquez et al. (2017) recommends the application of this index for
the analysis of connectivity due to its capacity to reect habitat loss and
landscape fragmentation.
From the previously performed MSPA analysis, a network composed
of cores and bridges can be extracted, without considering the rest of the
analysis classes (Vogt, 2016). In order to analyze the importance of
connectivity, the signicance of cores and links is studied using the dPC
index (Percentage variation in Probability of Connectivity). This index
measures the percentage reduction in connectivity that would occur due
to the loss of a given core or link (Saura and Rubio, 2010).
This analysis has been carried out for the 5 scenarios (actual pro-
posed scenarios “levels 1–4”) mentioned above with 3 different edge
sizes (Pixel 1, 2 and 3) for each scenario.
3. Results and discussion
3.1. Natura 2000 network layout
Once the interpolation method has been implemented, a value map
of importance for biodiversity (V.I.B.) is generated, which is linked to
the map of the areas of the Natura 2000 Network in Andalucía and
Castilla y Le´
on (Fig. 4) (Rinc´
on et al., 2019).
These maps show the degree of correspondence between the values
of importance for biodiversity in Andalucía and Castilla y Le´
on and the
boundaries of Natura 2000 Network. In this way, it is possible to verify
the disposition of the territories according to pre-established criteria of
great importance for conservation (Rinc´
on et al., 2019).
The maps analysis indicates that not all regions with a high biodi-
versity value are currently included in the Natura 2000 Network and
therefore, through this work, it has been possible to develop a clear and
concise methodology for a correct zoning of the Natura 2000 Network in
relation to the conservation of natural areas with a signicant biodi-
versity value. According to Vel´
azquez et al. (2019) there is a relationship
between areas with higher species richness and areas with good
connectivity.
There are limitations to applying this methodology, the most
important of which is the state of the data, which can vary from state to
state, making unication more complicated. In addition, it should be
borne in mind that each country has its own data, possibly with different
grid sizes, and some data may be out of date.
3.2. Proposals for zoning of the Natura 2000 network
The relevance of this study is its application for an adequate man-
agement and conservation of the Natura 2000 Network in the member
states of the European Union, guaranteeing the natural resources of each
area. This facilitates planning for conservation or restoration measures
for protected natural areas. For this purpose, we will propose a uniform
and simple method, so that it can be extrapolated to any European
territory.
Following the application of the methodology explained in phase III,
4 levels of protection have been established (Figs. 5 and 6), ranging from
1 to 4, so that level 1 denotes the most exclusive zones, made up of the
spaces with the highest V.I.B., while level 4 has the greatest non-realistic
number of the potential areas for biodiversity conservation comprising
almost the whole province. Each one of the protection levels is over-
lapped with the areas of the Natura 2000 Network and are presented as
zoning proposal (Rinc´
on et al., 2019).
Based on the available data, new bounderies have been proposed
adding 1.600.000 ha under Natura 2000 network. In this way, the areas
included in the SCIs and SPAs have a certain V.I.B., and this can be seen
on the conclusions section (Rinc´
on et al., 2019).
This zoning has been done starting from the V.I.B. map generated in
the previous phases. Thus, it is quite consistent that the Natura 2000
Network does not cover all the proposed areas and that have a high
biodiversity interest value. On the other hand, it is possible to observe
zones that do not have a great V.I.B., and that are included in the Natura
2000 Network (Rinc´
on et al., 2019). As indicated in the methodology,
each of the proposals has been based on biodiversity criteria which
makes possible a clear vision of the territories of greatest importance in
terms of conservation and protection of the environment.
3.3. Structural connectivity analysis (MSPA)
Below are the maps and values obtained using the Guidos software
for the Natura 2000 Network and the different levels of protection ac-
cording to the value for biodiversity.
In this way, the maps represent the distribution of the elements
present in the MSPA analysis. This will make it possible to analyze the
greater or lesser connectivity depending on the patches and linking el-
ements and compare them with the entire territory of Andalucía and
Castilla y Le´
on.
It is important to know that as the number of pixels increases, there is
a notable increase in the surface of the edges and, as a result, the surface
of all the cores is reduced while the percentage of surface occupied by
the connectors (links, bridges, and ramications) has increased consid-
erably (Hernando et al., 2010).
The amount of perforations is insignicant, and with respect to the
connecting elements, they are limited and the ones that stand out the
most are the bridges and the ramications. At the level 1, the result is
quite like the current scenario. There is a clear abundance of elements
that are identied as cores. In addition, the surface area of isolated sites
Fig. 4. Classication of Value of Importance for Biodiversity (V.I.B.). Hatched areas belong to Natura 2000 Network.
V. Rinc´
on et al.
Ecological Indicators 129 (2021) 108024
7
is reduced compared to the previous scenario. This could be translated as
a poor improvement in connectivity.
On the other hand, there has been an increase in bridges, which are
the most important connections, since they are identied as the true
ecological corridors. About level 2, it is again repeated that most of the
territory studied is made up of areas identied as cores. This fact is quite
coherent, given that all the different levels are related to each other. At
this level, there is a minimal increase in cores. But it is important to
mention that the number of perforations has increased the surface of the
“background” inside a core which implies that the loss of habitat results
in the loss of species dynamics (Thompson et al., 2017). In addition, the
surface area of the isolated sites has been slightly increased, and the
surface area of the connectors has been reduced. Thus, level 2 would be
the most unfavorable scenario for biodiversity conservation and
connectivity.
In the level 3, the data obtained are very similar to level 2. In pixel 1
there is little increase in the cores, as well as the existing perforations in
these cores.
Finally, in scenario 4, there is a small increase in the areas distin-
guished as cores, as well as islands and perforations. However, what
acquires greater importance at this level is that there is an increase in
linking bridges, which are considered as ecological corridors and
therefore this scenario becomes very important. Therefore, level 4 is a
scenario that has a great signicance in relation to the conservation of
species biodiversity as well as improved connectivity, given the large
surface area of ecological corridors (bridges).
In general, we could say that, the new zoning favours the increase in
the number of existing cores. It seems that, because of this, perforations
Fig. 5. Zoning proposal levels for biodiversity conservation in Andalucía. Level 1 areas are the most valuable biodiversity zones and Level 4 areas have the lowest
value for conservation.
Fig. 6. Zoning proposal levels for biodiversity conservation in Castilla y Le´
on. Level 1 areas are the most valuable biodiversity zones and Level 4 areas have the
lowest value for conservation.
V. Rinc´
on et al.
Ecological Indicators 129 (2021) 108024
8
are also incremented. However, it should be noted that there is an
enhancement of connectivity as the number of links, bridges and rami-
cations rises. Level 1 is considered the most favorable zoning, given
that it is the one with the largest number of corridors and the largest area
of cores. On the other side, there is a slight reduction in the surface area
of isolated areas. For all these reasons, we could say that by means of this
method an enhancement of the connectivity of the Natura 2000 Network
can be provided.
Lastly, in the following table (Table 1), the MSPA data is shown, so
that the improvement produced by the levels of importance of biodi-
versity compared to the Natura 2000 Network can be noted more
accurately.
In appendix A all the tables related to the MSPA in Andalucía and
Castilla y Le´
on can be found.
What has been analysed here is the percentage of area occupied by
ecological cores and corridors, but the fact of having a greater number of
cores or corridors does not mean that these have a greater or lesser
importance. In other words, the number of ecological cores and corri-
dors that exists in the study area has been analysed, however not their
importance.
3.4. Analysis of connectivity importance (PC)
Maps shown at Fig. 7 were obtained based on the analysis of the
connectivity importance conducted in the previous phase (Saura et al.,
2011).
Firstly, the connectivity of the current Natura 2000 Network scenario
has been analysed. It is important to know that as the number of pixels
increases, there is a notable increase in the surface of the edges, and as a
result, the surface of all the cores is reduced while the percentage of
surface occupied by the connectors (links, bridges, and ramications)
has increased considerably.
Red areas can be identied as cores, while ecological corridors
(bridges) have a blue or greenish colouring (Saura et al., 2011) (Fig. 8).
As shown in the resulting map, if the pixel 1 map is analysed, there are
cores of a lower tonality. This means that they are cores of vital
importance, given that in addition to acting as habitats where different
species can perform their functions, they act as connectivity function
between the different cores.
On the other hand, the map shows evidence that level 1 is slightly
better than the current Natura 2000 scenario. This is due to the presence
of cores of vital importance, which in addition to acting as habitats
where the various species can carry out their functions, provide a con-
nectivity function between the distinct core areas, and also a larger
number of ecological corridors, all of it makes possible the survival of
the species.
The maximum value of ecological corridors at pixel 1 of this level is
approximately 0,48 in Andalucía and 0,49 in Castilla y Le´
on, while in
the current Natura 2000 scenario, the most important ecological
corridor is 0,045 in Andalucía and 0,0012 in Castilla y Le´
on, this implies
a substantial improvement in the importance of connectivity in Castilla y
Le´
on. We have already commented in this work on the importance of
ecological corridors, and a crucial difference is shown in the various
levels.
With respect to level 2, all the core areas acquire big signicance,
given that it is substantial to have ecosystems where the species perform
their vital functions. But on the other hand, no core of those presented
has a minimum importance for the improvement of connectivity.
In contrast, we see that the corridor with the greatest relevance has a
connectivity importance value of 0,19 in Andalucía and 0,612 in Castilla
y Le´
on, which is higher than the current Natura 2000 Network.
In short, level 2, considering not only corridors but also the core
zones, is the most unfavourable level for biodiversity conservation and
improved connectivity.
Level 3 is quite like level 1 with the difference that there is a larger
surface area of important cores, but on the other hand, as the number of
pixels increases, ecological corridors become more important than level
1.
Thus, the maximum connectivity value of ecological corridors at
pixel 1, of this level is approximately 0,21 and 1,36, being barely higher
than the current Natura 2000 scenario and level 2 being clearly lower
than the maximum connectivity value of ecological corridors at level 1.
However, at pixels 2 and 3, the ecological corridors obtain an approxi-
mate maximum value of 29 in Andalucía and near 3 in Castilla y Le´
on.
Fig. 7. Analysis of connectivity importance in Andalucía. Level 1. a) Pixel 1 b) Pixel 2 c) Pixel 3.
V. Rinc´
on et al.
Ecological Indicators 129 (2021) 108024
9
Therefore, we could conclude that it is important to take level 3 into
account for biodiversity conservation and improved connectivity.
Finally, level 4 is the most important for biodiversity conservation
(not with the higher V.I.B.) and improved connectivity. This is due to the
presence of core areas of essential signicance, which in addition to
acting as habitats where species can operate, exert a function of con-
nectivity between the various cores and also a greater number of surface
of ecological corridors, making possible the survival of species.
In this way it can be dened that the most important levels are 1,3
and 4, being proposed as a zoning that can optimise the conservation
and connectivity of the species of the current Natura 2000 Network.
From a planning perspective, they can be seen as bottlenecks and crucial
areas for species movement and as fragile elements that are likely to be
the rst to be affected by landscape changes and management decisions
(Saura et al., 2011). In Andalusia, the importance of the cores is lower at
all levels than the current importance. With respect to the ecological
corridors, in pixel 1 they acquire greater importance than the current
importance, however, in pixels 2 and 3 this importance is less, as the size
of the corridor is greater. The opposite occurs in Castilla y Le´
on, where,
as the level and pixel size increases, the importance of both nuclei and
ecological corridors increases. Comparing both cases, this methodology
is better adapted for Castilla y Le´
on, although if we take into account
that the areas with the highest value are those at level 1, the method-
ology works for both territories.
Connectivity is one of the most important aspects to take into ac-
count when assessing the conservation status of Natura 2000 habitats
and sites (Hernando et al., 2017). Species richness in each habitat patch
(local) and in the entire network (regional) declines as habitat is lost
(Thompson et al., 2017).
Lastly, in the following tables (Tables 2 and 3), the importance of
connectivity data is attached, so that the improvement produced by the
levels of importance of biodiversity compared to the Natura 2000
Network can be noted more accurately.
The results obtained can be assimilated to those obtained by Saura
et al. (2011), who used the PC-innity index, in which an increase in
bridge connectivity also increases the possibility of species moving from
one core to another.
The limitations mentioned above must be taken into account
(different grid sizes, outdate data, etc…). If the data is unied in all the
Fig. 8. Zoom to PC Index. Cores are red and bridges are blue. (For interpretation of the references to colour in this gure legend, the reader is referred to the web
version of this article.)
Table 2
Analysis of the connectivity importance data (PC) in Andalucía.
Connecting
elements
Analysis of the connectivity importance data (PC): Pixel 1
Natura 2000
network
Level 1 Level 2 Level 3 Level 4
Cores −0.052 −0.4768 −0.194 −0.1145 −0.41993
Ecological
corridors
0.045 0.47726 0.194 0.207012 0.7045
Connecting
elements
Analysis of the connectivity importance data (PC): Pixel 2
Natura 2000
network
Level 1 Level 2 Level 3 Level 4
Cores −0.789 −0.2707 −2.774 −2.3093 −2.3093
Ecological
corridors
29.9 0.4514 2.774 29.2491 29.2491
Connecting
elements
Analysis of the connectivity importance data (PC): Pixel 3
Natura 2000
network
Level 1 Level 2 Level 3 Level4
Cores −4.602 −0.6305 −3.852 −6.294 −5.1046
Ecological
corridors
29.96 0.4333 2.71 29.332 27.9397
Table 3
Analysis of the connectivity importance data (PC) in Castilla y Le´
on.
Connecting
elements
Analysis of the connectivity importance data (PC): Pixel 1
Natura 2000
network
Level 1 Level 2 Level 3 Level 4
Cores −0.0011 −0.0254 −0.0008 −1.3614 −0.4022
Ecological
corridors
0.0012 0.0439 0.0612 1.3614 0.4934
Connecting
elements
Analysis of the connectivity importance data (PC): Pixel 2
Natura 2000
network
Level 1 Level 2 Level 3 Level 4
Cores −0.002 −0.0047 −0.0072 −2.6028 −4.0881
Ecological
corridors
0.003 0.0033 0.0115 2.6026 4.0006
Connecting
elements
Analysis of the connectivity importance data (PC): Pixel 3
Natura 2000
network
Level 1 Level 2 Level 3 Level4
Cores −0.0021 −0.0054 −0.0075 −2.8491 −29.7768
Ecological
corridors
0.031 0.0044 0.0184 2.7955 29.8441
V. Rinc´
on et al.
Ecological Indicators 129 (2021) 108024
10
countries with Natura 2000 sites, the connectivity of all these sites at
European level would be improved, achieving the objectives of the
Natura 2000 Network.
4. Conclusions
The member countries of the European Union have been disorga-
nized in identifying conservation areas, due to the lack of clear guide-
lines for selecting protected areas. Despite this, attempts have been
made to establish optimal selection criteria by developing different
methodologies according to different approaches.
For this purpose, in this study, the conservation of biological di-
versity has been used as a point of view, so that the results obtained
show areas of high value for the conservation of this diversity. Using the
principle of spatial planning for conservation in designing the Natura
2000 network, can generate an optimum network for species conser-
vation, as it was foreseen in the EU Directive (Niculae et al., 2016). This
methodology allows the establishment of uniform and coherent criteria
that can be easily considered by the member countries of the European
Union, so that the process of evaluation and assignment of protected
areas can be consolidated. It’s important to maintain functional con-
nectivity outside administrative boundaries in order to maintain Natura
2000 habitats and to avoid isolated cores (Estreguil et al., 2013).
It is possible to state that in this study the location of the protected
sites is very similar to the results obtained from the evaluation of the
biodiversity criteria. This means a zoning very close to the optimum has
been achieved, despite the fact that areas have been identied that
should be protected and yet they are not.
Likewise, the importance of the proposed new zoning lies in
improving connectivity between protected spaces. The new zoning
covers more areas of interest for biodiversity, as well as zones of great
importance in relation to connectivity. In this manner, the most
important ecological cores and corridors that allow the protection of
biodiversity are catalogued.
In any case, the relevance of the implementation of this assessment
lies in the appropriate land management by the European Union mem-
ber countries, which supports sustainable development through the
establishment of conservation areas that guarantee the necessary natu-
ral resources. It also facilitates compliance with European environ-
mental policy.
CRediT authorship contribution statement
Víctor Rinc´
on: Formal analysis, Methodology, Writing – original
draft. Javier Vel´
azquez: Conceptualization, Project administration,
Investigation, Methodology, Formal analysis, Writing – original draft.
Javier Guti´
errez: Formal analysis, Writing – review & editing. Ana
Hernando: Data curation, Writing – review & editing. Alexander
Khoroshev: Data curation, Writing – review & editing. Inmaculada
G´
omez: Data curation, Writing – review & editing. Fernando Herr´
aez:
Data curation, Writing – review & editing. Beatriz S´
anchez: Data
curation, Writing – review & editing. Juan Pablo Luque: Data curation.
Antonio García-abril: Data curation, Writing – review & editing.
Tom´
as Santamaría: Data curation, Writing – review & editing. Daniel
S´
anchez-Mata: Writing – original draft.
Declaration of Competing Interest
The authors declare that they have no known competing nancial
interests or personal relationships that could have appeared to inuence
the work reported in this paper.
Appendix A. Supplementary data
Supplementary data to this article can be found online at https://doi.
org/10.1016/j.ecolind.2021.108024.
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