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Geomorphology 461 (2024) 109298
Available online 9 June 2024
0169-555X/© 2024 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).
Exploring the Correlation between Geoheritage and Geodiversity through
Comprehensive Mapping: A Study within the Sesia Val Grande UNESCO
Global Geopark (NW Italy)
Michele Guerini
a
,
b
,
*
, Alizia Mantovani
c
, Rasool Bux Khoso
a
, Marco Giardino
a
a
Earth Science Department, University of Turin, Via Valperga Caluso, 35, 10125 Torino, Italy
b
EDYTEM, Universit´
e Savoie Mont Blanc, 5 Bd de la Mer Caspienne, 73370 Le Bourget-du-Lac, France
c
Computer Science Department, University of Turin, C.so Svizzera, 185, 10149 Torino, Italy
ARTICLE INFO
Original content: Geodiversity and Geoheritage
data from Alagna Valsesia, Sesia Val Grande
UGGp (NW Italy) (Original data)
Keywords:
Geoheritage
Geodiversity map
Spatial correlation
Geostatistics
Geotourism
Alps
ABSTRACT
While geoheritage and geodiversity have been well dened in the literature, the multiplicity of denitions given
to these two concepts makes it difcult to establish an unambiguous relationship between them. Basing on
semantic-ontological studies, this study aims to reduce this ambiguity within the concepts by investigating the
relationship between the geodiversity richness and the presence of geoheritage, and discussing whether the areas
with the greatest geodiversity are the ones with the most relevant geoheritage, thus questioning the potential use
of the geodiversity index map. Upon a strong theoretical framework, a quantitative geodiversity index map was
created for the Alagna Valsesia municipality, within the Sesia Val Grande UNESCO Global Geopark (Italian
Western Alps). Then, 25 geosites were identied and mapped in the same area. Notably, the exploration into the
correlation between geodiversity and geoheritage on the eld shows that in our study area there is no spatial
correlation between the geodiversity class and the number of geosites, proving that some geosites may occur in
areas of low geodiversity and the greatest geodiversity are not the ones with the most relevant geoheritage.
Moreover, all the non-parametric regression models tested are not signicant, indicating that there is no pre-
dictable relationship between geodiversity and geoheritage in Alagna Valsesia (NW Alps). For that reason, our
work highlights that although the quantitative geodiversity map can have an important role for geoconservation
and within biodiversity studies, it could not be a strong tool for geosites recognition and tourism promotion,
while for this purpose should be better use a qualitative geodiversity map. Finally, the potential use of the
geodiversity map depends on the purpose of the study and the approach used to produce it. For a comprehensive
geoconservation and geoheritage promotion strategy, the two approaches (qualitative and quantitative) may be
complementary.
1. Introduction
In recent years, there has been considerable interest in the applica-
tion of the geodiversity concepts within sustainability and environ-
mental studies. The importance of geodiversity for the sustainable
management of territories has been generally recognized (Hjort and
Luoto, 2012; Brilha et al., 2018; Schrodt et al., 2019), as well as the need
to protect geodiversity from the new challenges of climate change
(Gordon et al., 2022). However, the potential and usefulness of geo-
diversity assessment is still under debate within the scientic commu-
nity (Zwoli´
nski and Stachowiak, 2012; Hjort et al., 2015; B´
etard and
Peulvast, 2019; Brocx and Semeniuk, 2019, 2020; Gray and Gordon,
2020; Crisp et al., 2021; Gray, 2021; Gonçalves et al., 2022).
Over the past two decades, a large number of studies have contrib-
uted to the proposal and improvement of new geodiversity assessment
methods (Benito-Calvo et al., 2009; Zwoli˜
nski, 2009; Hjort and Luoto,
2010; Pereira et al., 2013; Argyriou et al., 2016; Forte et al., 2018; Crisp
et al., 2021; Gray, 2021). According to Zwoli´
nski et al. (2018) there are
three methods for assessing geodiversity: the qualitative approach, the
quantitative one and the combination of the both (quali-quantitative
approach). The qualitative approach relies primarily on the expertise
and experience of a single or group of subject-matter experts (a
descriptive method based on the expert assessment of geodiversity of a
certain area) (e.g. Panizza, 2009; Seijmonsbergen et al., 2014). Results
* Corresponding author at: Earth Science Department, University of Turin, Via Valperga Caluso, 35, 10125 Torino, Italy
E-mail addresses: michele.guerini@unito.it, michele.guerini@univ-smb.fr (M. Guerini).
Contents lists available at ScienceDirect
Geomorphology
journal homepage: www.journals.elsevier.com/geomorphology
https://doi.org/10.1016/j.geomorph.2024.109298
Received 15 November 2023; Received in revised form 1 June 2024; Accepted 4 June 2024
Geomorphology 461 (2024) 109298
2
are graphically represented by maps, which in turn are based on a very
good knowledge of the same area, by both eld studies, remote sensing
and a thorough study of the literature (Zwoli´
nski and Stachowiak, 2012;
Seijmonsbergen et al., 2018; da Silva and do Nascimento, 2020; Jan-
kowski et al., 2020). However, this makes the qualitative approach
somewhat subjective, and leads to a number of problems, such as the
difculty in standardising a unique method, and suitability with only
nominal data (Zwoli´
nski et al., 2018; Crisp et al., 2021).
Quantitative approach is based on the numerical analysis of a group
of variables typically used to calculate geodiversity indexes, such as the
number of geological unit or the number of soil types. These are inten-
ded to numerically reect and map the spatial variability of various
abiotic components of geodiversity within a certain area (Datta, 2022).
With respect to the qualitative approach, the quantitative one is
considered less subjective and therefore capable of improving the
comparability of results with other areas, which is an important aspect
of geodiversity estimation (Serrano et al., 2009; Hjort and Luoto, 2010;
Pereira et al., 2013; Santos et al., 2017; Araujo and Pereira, 2018; Forte
et al., 2018; da Silva et al., 2019; Fern´
andez et al., 2020; Ahmadi et al.,
2021).
Within literature, few studies discussed the overall value and general
applicability of geodiversity assessment, mostly recognising that some
methods are more appropriate in some situations than others (Gonçalves
et al., 2022; Najwer et al., 2022). However, the best method can be
difcult to determine, because it depends on the specic conditions,
such as the geology and available geospatial data (Gonçalves et al.,
2020). According to Zwoli´
nski et al. (2018), the best method is some-
where in between the qualitative and quantitative approaches. In this
perspective, the quantitative assessment of geodiversity has to be sup-
plemented with new data from the initial expert evaluation; therefore,
elements with qualitatives value such as aesthetic, scientic, and
educational values can be taken into account (Zakharovskyi and
N´
emeth, 2021a). Nevertheless, the assessment, quantication and
mapping of geodiversity still have some limitations, mostly because
there are no uniform standards or assessment methods (Soms, 2017;
Ib´
a˜
nez et al., 2019). Further, it remains unclear if the gap between
methodology and concepts has been bridged in recent studies. Indeed,
the numerous gediversity assessment methods present mutual in-
consistencies, highlighting the many ways in which the basic concept
can be interpreted and applied (Crisp et al., 2021). In order to achieve a
meaningful assessment of geodiversity, it could be recommended to
focus on standardising the criteria to be included in the assessment, as
well as developing a common methodology and a model that includes
the interaction of all geodiversity-related variables (Perotti et al., 2019).
Several studies aimed to highlight the importance of the assessing
geodiversity, showing the inuences of abiotic elements on biotic ele-
ments in the natural environment (K¨
arn¨
a et al., 2018; dos Santos et al.,
2019; Zarnetske et al., 2019; Fern´
andez et al., 2020; Datta, 2022), and
concerning the provided services to society (Fox et al., 2020). Some
authors also stressed the importance of assessing geodiversity to eval-
uate geoheritage and consequently foster geoconservation (B´
etard and
Peulvast, 2019; Najwer et al., 2023), but only a little attention has been
paid to the need of establishing a robust and unambiguous conceptual
framework for fully developing the potential of the geodiversity index
map.
This study aims to investigate the relationship between the geo-
diversity richness in the area and the presence of geoheritage, discussing
whether the areas with the greatest geodiversity are the ones with the
most relevant geoheritage. This led to question the potential use of the
geodiversity index map. While geoheritage and geodiversity have been
dened in the literature, the multiplicity of denitions given to these
two concepts, particularly for geoheritage (see Brocx and Semeniuk,
2007; Mantovani, 2024), makes it difcult to establish an unambiguous
relationship between them. Based on semantic-ontological studies
(Mantovani and Lombardo, 2022; see Section 3), our study aims to
investigate this relationship in the eld by using maps in an attempt to
reduce this ambiguity within the concepts. Our investigation delves into
the understanding of the complex connections between geodiversity and
geoheritage within Alagna Valsesia (NW Italy, Fig. 1), a region recog-
nized for its signicant scientic and cultural importance located within
the Sesia Val Grande UNESCO Global Geopark (http://www.sesiavalgra
ndegeopark.it/index.php/it/). Through the parallel production of maps
of geodiversity and geosites, our study aims to support policy makers,
geopark staff and tourism planners in promoting responsible geotourism
practices and sustainable development in the Sesia Val Grande UNESCO
Global Geopark.
2. Study Area
For this work we chose Alagna Valsesia as case study area. Alagna
Valsesia is a municipality with a territory that ranges from 1140 to 4554
m a.s.l., and located in the upper part of the Sesia main Valley, in
Piedmont Region (NW Italy) (Fig. 1), where the Sesia river ows
through. From there, ve tributary valleys extend: to the west lies Val
Vogna, Val d'Otro, Valle d'Olen and Valle di Bors, while Valle di Mud lies
to the east. The landscape comprises some of the highest peaks of the
Monte Rosa Massif, that surround the valley basin and are signicant for
international alpinism. The highest of these peaks is Punta Gnifetti, at
4554 m above sea level. From a geological point of view, Alagna Valsesia
is located at the boundary between Austroalpine and Pennidic Domains
(nappes) of the Alpine chain (Dal Piaz et al., 2015; Piana et al., 2017).
The Pennidic Domain is composed of continental crust units, which were
derived paleogeographically from the distal margin of Europe, as well as
oceanic crust units that originated from the Piedmont-Ligurian Ocean
(Dal Piaz et al., 2003). Particularly, the continental crust is represented
by the Monte Rosa Unit, in which micaschists and ortogneiss outcrop;
while the oceanic crust is represented by two different Units: the Pied-
montese Zone Combin type, in which calceschists and metabasites
outcrop, and the Piedmontese Zone Zermatt-Saas type, characterized by
metabasites and serpentinites (Servizio Geologico Italiano, 1951; Dal
Piaz, 2001). Finally, Austroalpine Domain is represented by the Sesia-
Lanzo Zone, that emerges only in the southernmost part of the study area
and is composed of gneiss (Fig. 2).
The geological richness of the area is complemented by its signicant
geoheritage sites (Viani et al., 2020), making it the proper place to
investigate and clarify the meanings of important terms like geo-
diversity, geoheritage and geosites. The basic shape of the Monte Rosa
Massif and the valleys within Alagna Valsesia is the result of endogenous
and exogenous geological processes, such as the Alpine orogenesis
(which set the litho-structural and tectonic conditions) and morphocli-
matic variations (e.g., glacial pulsation). Particularly, during the Qua-
ternary, the glaciers were the main morphogenetic agent in the area, and
even today the dominant processes at higher altitudes (above 2600 m a.
s.l.) are glacial and periglacial (Carraro and Giardino, 2004; Smiraglia
and Diolaiuti, 2015). Nevertheless, at lower altitudes there is a progla-
cial environment whose actual surface shape results from active pro-
cesses, where the main morphogenetic agents are currently uvial (with
the presence of the Sesia river) and especially gravitational ones (Giar-
dino et al., 2017) (Fig. 3).
Additionally, in Alagna Valsesia is present the Walser people. The
Walsers are a local community established in Alagna Valsesia since the
Middle Ages following long migrations and known for maintaining their
centuries-old traditions and their resilience in the face of climate
changes (Dal Negro, 2004; Lenz, 2007; Rizzi and Gianoglio, 2023). Their
culture and traditions adds another layer of cultural signicance to the
area.
Due to the geological diversity, geomorphological signicance, and
cultural importance of Alagna Valsesia, it has gained acknowledge
among scientic community on an international level, being included in
the Sesia Val Grande UNESCO Global Geopark, aiming to develop
informal education, geoconservation and geotourism strategies (Henri-
ques and Brilha, 2017); by receiving the European Heritage - Europa
M. Guerini et al.
Geomorphology 461 (2024) 109298
3
Fig. 1. a) Geographic location of Alagna Valseisa municipality, within the Piemonte Region, Italy. b) Overview map and detailed hillshade of Alagna Valsesia
municipality, located at the end of the Sesia valley, at the border with the Aosta valley and Switzerland.
Fig. 2. Simplied geolithological map of the Alagna Valsesia municipality. The original map was made with the land use plan purpose.
(Modied from Bartolini et al. (2023a, 2023b))
M. Guerini et al.
Geomorphology 461 (2024) 109298
4
Nostra Awards in 2014 for the conservation of traditional architecture
(https://www.europanostra.org/winners-2014-eu-prize-cultural-herita
geeuropa-nostra-awards-announced/); and being designed by the
H2020 Arctic Hub project as a learning study area in the Alps reects its
remarkable diversity and cultural heritage, as well as its importance on a
European scale (https://projects.luke./arctichubs/). Moreover Alagna
Valsesia was the subject of several research, such as the study of geo-
system services in mountain areas (Tognetto et al., 2021), works aimed
at studying the impacts of climate change on natural elements of geo-
diversity (Colombo et al., 2019; Giardino et al., 2020; Quaglia et al.,
2020), and an important site for geotourism (Perotti et al., 2020) and
geoeducational activities (Giardino et al., 2022). Together, these ele-
ments make Alagna Valsesia a suitable case study for advancing our
knowledge on geodiversity and geoheritage of the region, how they
relate to one another, and the consequences of these relationships for
promoting sustainable development and geotourism.
3. Teorethical background
The assessment of geodiversity is an important issue which is still
under debate. Indeed, there are different methods for the assessment
that have been applied for different purposes and different types of
areas. In order to support a more coherent study on the eld concerning
both a geodiversity assessment and the relation of the geodiversity
richness with the occurrence of geoheritage, we propose a summary of
the denitions of these concepts based on the semantic and ontological
studies (see Mantovani and Lombardo, 2022). Especially, these ap-
proaches focus on formalizing concepts within a given knowledge
domain and make their relationships explicit (Gruber, 1993).
Specically, some of the concepts considered in our work are described
in literature with many different denitions (Brocx and Semeniuk,
2007) that can be different and mutually incoherent. Accordingly,
ontological and semantic studies allow to reduce ambiguities among the
considered concepts and served as the core basis for our eld assess-
ments and analyses focused on understanding the correlation between
geodiversity and geosites within our study area.
3.1. Geodiversity
Over the past 30 years, several denitions of the concept of geo-
diversity have been proposed. According to Boothroyd and Henry
(2019), the many denitions can be grouped into two main schools of
thought according to the afnity of the concepts within them. The rst
school of thought follows the denition rst suggested by Gray (2013)
and Gray et al. (2013); while the second school of thought follows a
denition proposed by Brocx and Semeniuk (2007) after Semeniuk
(1997) (Mantovani, 2024). Upon analyzing the denitions, the main
difference lies in the relation to a territory. Brocx and Semeniuk's (2007)
denition suggests a limited use of the concept to a well-dened area,
while Gray (2013) describes geodiversity at a global scale and species
how it can be considered at both global and local levels. According to
Boothroyd and Henry (2019) 88 % of authors use Gray's denition or
similar versions. Consequently, our work is based on this denition of
geodiversity. Therefore, in the context of our study, we considered as
elements of geodiversity the ones listed in this denition, many of which
are already encoded in the OntoGeonous ontology (Lombardo et al.,
2016, 2018; Mantovani et al., 2020a, 2020b), an ontology for the geo-
sciences based on GeoScienceML international standard (http://geos
Fig. 3. Geomorphological map of Alagna Valsesia including glacial, gravitational, uvial and structural landforms. The original map was made with the land use plan
purpose.
(Modied from Bartolini et al. (2023a, 2023b))
M. Guerini et al.
Geomorphology 461 (2024) 109298
5
ciml.org/). Specically, these elements are the geological features in the
whole, considering the materials (rocks, minerals, fossils, soils, but also
water); in which shape they appear on the surface (landforms, structures
and topography); and the presence of processes that act on the surface or
the evidence of subsurface processes.
3.2. Geoheritage
As for geodiversity, the concept of geoheritage has several denitions
in literature (see Mantovani, 2024). All of these denitions highlight the
deep relationship between geoheritage and the elements of geodiversity.
Moreover, all of these denitions share the attribution of a value to the
elements of geodiversity as a requirement for geoheritage status. All
these denitions are well summarized in the denition suggested by
Sharples (2002). Indeed, it encompasses all the other denitions when
considering the relationship with the geodiversity elements and values.
However, looking at denitions and works in the literature lists of values
to dene geoheritage are not fully shared (Sharples, 2002; Brilha, 2018;
Georgousis et al., 2021; National Park Service, 2021). For example, all
the authors accept the scientic value as a condition for an element of
geodiversity to be considered as geoheritage, but not all of them accept
the recreational or economic values (see Mantovani, 2024). An example
of this issue is Uluru/Ayers Rock, located in Uluru-Kata Tjuta National
Park, Australia. Although its scientic value has been established
(Twidale, 1978, 2010; Twidale and Wopfner, 1981), this geosite is often
associated with its high cultural value (e.g. Brilha, 2018). However,
cultural value alone is not generally accepted for attribution of geo-
heritage status. As the values that comprise the geoheritage only
partially overlap, we have adopted the Sharples (2002) denition
because it avoids constraints on given values and allows for the inclusion
of all other denitions, so being supportive for decision-makers.
3.3. Geosites
Despite also the term geosite present multiple denitions in litera-
ture (see Mantovani, 2024), all these denitions highlight that a geosite
is a delimited area in which signicant geodiversity elements are pre-
sent. According to some denitions (García-Cort´
es et al., 2013; Brilha,
2016) the geosites have a direct connection with the geoheritage (i.e.,
geosites are the in situ occurrence of geoheritage), while others identify
in the geosite the presence of geological interest (Wimbledon, 1995;
Brilha, 2018). However, also in the latter denitions, the link between
geosites and geoheritage is established by relating geological interest
and values (that are condition for an element of geodiversity to be
considered geoheritage), as investigated by Diaz Martinez and Fernan-
dez Martinez (2015) and by others ongoing studies. For instance, the
geosite of the Vajont Landslide could be examined: in the Vajont Valley,
in Northern Italy, a massive landslide occurred in 1963. It is a geosite of
international relevance, characterized on the one hand by the geo-
morphologic interest due to the exposition of the sliding surface and of
the crown, that can be linked to a scientic value for the landslide study;
on the other hand by the historical and educational interest for the
signicance of that event in the history of the region, giving cultural and
educational values (Hilario et al., 2022). For the purposes of our study,
we consider the geosites in the eld as areas in which geoheritage occur,
and all of the reviewed denitions allow to link the geosites to the
geoheritage. Thus, it is possible to investigate the relationship in the
eld between geodiversity richness and geoheritage, through its
occurrence in the identied geosites.
4. Methods
The present study entails the identication and mapping of geo-
diversity and geosites within Alagna Valsesia, and the spatial correlation
between these two elements. Additionally, the potential utility of the
geodiversity assessment map for identify geosites is discussed. In
particular, geotourism is increasingly gaining interest (Herrera-Franco
et al., 2020), and Alagna Valsesia, as mountain tourist area within a
UNESCO Global Geopark, is an important place where to plan geo-
tourism activities for sustainable development. To address these
research questions we created the geosites map and the quantitative
geodiversity index map; then we overlapped them and applied non-
parametric correlation tests to investigate their correlation.
First, we identied the geosites that represent the main attraction of
the Geoparks (Brilha et al., 2018). The identication of geosites was
conducted by analyzing the geoscience literature related to the most
important study area and then completed by photo interpretation and
some relevant eld trips. Secondly, by means of spatial analysis using
geographic information system (GIS) with an open source software QGIS
(version 3.28.13, https://www.qgis.org/en/site/), we assessed geo-
diversity and mapped the geodiversity index in the study area using a
revised version of the method previously described in Forte et al. (2018).
The method was adapted to also consider elements such as quarries and
mines, and the natural processes active in the study area during the
geodiversity assessment (further addressed as energy relief). Subse-
quently, in an attempt to understand the correlation between geo-
diversity and geoheritage, we overlaid the geodiversity index map and
the geosites map, and applied some correlation tests using RStudio
software, version 2023.12.1 +402 (https://posit.co/download/rstudio
-desktop/). Finally, to better understand the type of relationship
describing the spatial relationship between these two variables, we
performed some non-linear regression models.
4.1. Geosites selection
The method of identifying and selecting the geosites of Alagna Val-
sesia was based on a two-step approach. First, we consulted the existing
literature on the local geosites. Perotti et al. (2020) provided a foun-
dational inventory of geosites within the Sesia Val Grande UNESCO
Global Geopark, serving as a key reference for Alagna Valsesia geosites.
Additionally, in order to identify more geosites in the study area, we
investigated through the Sesia Val Grande geopark's archives, which
listed sites of particular geological interest in Alagna Valsesia; the
“Inventario Nazionale dei Geositi”, the ofcial inventory of all geosites
catalogued in Italy provided by the Italian Institute for Environmental
Protection and Research (ISPRA-Servizio Geologico d'Italia, 2023); and
other articles about the geosites of the Sesia Val Grande UNESCO Global
Geopark (Perotti et al., 2019; Guerini et al., 2023). Second, through
photointerpretation and eld trips, we completed the selection of geo-
sites by adding to those identied in the literature some geosite that,
following the criteria outlined in Section 3.3, have similar level of in-
terest. During the eld trips we also meticulously recorded geographic
coordinates of the geosites, enabling accurate spatial representation of
each geosite in GIS environment.
4.2. Geodiversity assessment
Geodiversity assessment is difcult due to its complexity, and it is
impossible to consider the diversity of all the abiotic elements (Marceau,
1999). Therefore, it was necessary to make a selection based on the
purpose of the study. Among the geodiversity elements listed in the
denition by Gray (2013), geology, geomorphology, soils, and hydrog-
raphy were considered. According to Bollati et al. (2023), these are
relevant elements of geodiversity, mainly because Alagna Valsesia is a
mountainous area, and geodiversity of proglacial areas depends on
water, rocks, landforms and soils. In addition, we also considered the
quarries and mines and energy-relief. The former increase the diversity
of an area by ensuring the inclusion in the index of minerals, stones and
metals present in the area. Indeed, quarries and mines expose a range of
rock types that would not otherwise be visible (British Geological Sur-
vey, 2024). Moreover, they have also been considered an element of
geodiversity and are often linked to the geological heritage of the area
M. Guerini et al.
Geomorphology 461 (2024) 109298
6
(Gajek et al., 2019; Kubalíkov´
a and Balkov´
a, 2023). The latter make it
possible to highlight places where processes, which are part of the
denition of geodiversity (Gray, 2013), may be most intense. A geo-
database was created for each of these types of elements.
For our study we crossed information coming from many different
geodatabases:
•Lithology: contains the information included in the geolithogical
map of Alagna Valsesia (Bartolini et al., 2023a), naming all the
different lithological units;
•Geomorphology: contains the following elements selected from the
geomorphology map made for the land-use plan of Alagna Valsesia
(Bartolini et al., 2023b): glaciers, moraines, glacial deposits, faults,
landslide landforms (niches, body and deposits), slope debris, allu-
vial deposits, and terraces. In addition, this dataset includes energy
relief information, which contains the polygons where energy relief
was considered maximum (from ve classes, only the highest was
selected because it includes areas where there is more energy and
therefore it is more likely to have active natural processes);
•Hydrography: includes information about the river network classi-
ed according to the Strahler method for hierarchization of uvial
channels within a drainage system (Strahler and Archibold, 2011). In
addition, it includes information about other elements linked to the
hydrographic network: conoids, springs and lakes;
•Soils: contains the soil types;
•Quarry and mines: contains information on mineral, stone and metal
resources within Alagna Valsesia, both active and inactive.
The Municipality of Alagna Valsesia provided the geolithogical and
geomorphological maps at 1:10,000 scale (Bartolini et al., 2023a,
2023b). From Piedmont Geoportal (https://www.geoportale.piemonte.
it/cms/) we retrieved the 5-meter resolution Piedmont DTM (for
extraction of Alagna DTM and for calculation), and both the hydro-
graphic map at 1:10,000 scale and the soil map at 1:250,000 scale for
regional framework of local soil types. The mineral data were provided
by the Sesia Val Grande UNESCO Global Geopark archive. All these
maps, except for DTM, were obtained in shapele format and have been
checked and validated in QGIS as a means of avoiding any topological
error such as superimposition.
Each of the databases was loaded into QGIS in shapele format, some
in point and some in polygonal format (see Table 1). In order to carry out
the geodiversity assessment, all polygons were converted to point fea-
tures using the centroid tool in QGIS (thus getting one point for each
polygon). Later on, all the punctual shapeles were merged together,
thus providing a single shapele in which each point represent one
element of the geodiversity. Eventually, we performed the kernel anal-
ysis on this shapele that outcome in a nal raster le. Indeed, this
method avoids the use of the cells which can be difcult to apply to small
areas, such as the one under study, and can depend on numerous tests
(Lopes et al., 2023). Thereafter we classied the resulted raster into 5
classes of geodiversity (from very low to very high) according to the
Jenks Natural Breaks method (Jenks, 1967). These characterization of
geodiversity is relative to the study area and should not be understood as
absolute values (Gonçalves et al., 2020). Thereby, the values of the
kernel density are directly the values of the geodiversity index. To obtain
the more accurate result we conducted several tests in the kernel anal-
ysis changing the radius value. By doing tests with 100 m, 250 m, and
500 m radius, we were able to choose the 250 m radius as the optimum
value for our case study, also in accordance to Forte et al. (2018).
4.3. Geodiversity and Geoheritage correlation
To achieve the aim of our research understanding the links between
geoheritage and geodiversity by testing their spatial correlation, the
geodiversity index map and the geosites (point feature) map were
overlaid. By using the Point Sampling Tool QGIS plugin (version 0.5.4
https://plugins.qgis.org/plugins/pointsamplingtool/) we identied the
geodiversity value at the locations of each selected geosite. Then, we
reclassied the values as we previously did for the geodiversity assess-
ment, and assessed to which geodiversity class each geosite belongs.
The nal statistical analysis has been performed by using Rstudio
open source software and considered the count of geosites in each
geodiversity class. Standard Pearson correlation test (Lee Rodgers and
Wander, 1988) were not applicable due to the quantitative nature of the
geosite variable and the ordinal and qualitative nature of the geo-
diversity class variable. Moreover, the Shapiro-Wilk normality test
(Shapiro and Wilk, 1965), applied to the geosite number variable,
resulted W =0.93017, with a p-value =0.5975, indicating that it is not
possible to assume the normality distribution, that is required for the
signicance of the Pearson test.
Non-parametric correlation tests were conducted to ascertain the
absence of a positive linear correlation between the number of geosites
and the geodiversity class. We applied both the Spearman and Kendall
rank correlation tests (Spearman, 1904; Kendall, 1938; Dodge, 2008)
because these non-parametric tests take into account the different
characteristics of our ordinal qualitative and quantitative data, allowing
us to examine the relationship between variables while avoiding the
assumptions of linearity and normality (Siegel, 1957). Finally, having
acknowledged the non-linear relationship, an attempt was made to nd
the best non-linear regression model to appropriately determine the
relationship between these variables. This involved examining
numerous non-linear regression models to identify the model that best
represented the complex relationship between geodiversity class and
geosite quantity.
4.4. Limitations of the method
The complexity of the mountain environment, which is rich in geo-
diversity, poses challenges. As a mountainous area, with altitudes
ranging from 1140 to 4554 m above sea level, the region has experi-
enced rapid climate change, with the transition from the Little Ice Age
(from about 1250 to 1860 CE) to a period of warming, which has
intensied geomorphological processes (Giardino et al., 2017, 2020).
Due to the resulting complex topography and geological processes, it
may be difcult to directly correlate geomorphological elements with
the structural pattern (such as faults and folds). In addition, automated
techniques in GIS software are not able to fully capture this complexity
and have to make compromises. To address these limitations, future
research should include comparative analyses in areas where correla-
tions are more evident. Such efforts provide relevant background in-
formation and clarify the connections between geoheritage and
geodiversity in less complex situations than our study area.
Moreover, concerning the scale of the maps, for consistency with the
size of our study area, we chose to consider maps with 1:10,000 scale. By
doing this, we were able to conduct an accurate assessment of geo-
diversity at local scale and compare the geodiversity classes location in
the area with the position of the selected geosites. It is recognized that
the soil map in the source datasets is not at 1:10,000 scale but at
1:250,000. Although it would be better to have all maps at the same
scale to have the same detail in all features considered, it was not
Table 1
Number of the elements and format type of the datasets resulted from the data
collection of the geodiversity elements in Alagna Valsesia. E.g., Lithology
dataset contains the polygons of the specic geological lithostratigraphy unit.
Dataset Number of elements Type of shapele
Lithology 112 Polygons
Geomorphology (+energy relief) 682 Polygons
Soils 18 Polygons
Hydrology 250 Points and Polygons
Quarry and Mines 7 Points
M. Guerini et al.
Geomorphology 461 (2024) 109298
7
possible to obtain a soil map at a larger scale. For this reason, we decided
that including the 1:250,000 in the assessment was rather better for the
nal result than not including the soil elements.
Finally, while we rigorously followed established protocols for
identifying geosites and consulted widely accepted literature, and al-
ways relied on the denition of a geosite (see Section 3.3), the nal
selection included some subjectivity inherent in the selection process.
This is because it is difcult to streamline the geological value and in-
terest included in the denition of geosite, and there is no fully shared
opinion in the literature on what values allow an element of geodiversity
to be given geoheritage status (see Section 3.2).
5. Results
Although it is generally accepted that the assessment and mapping of
geodiversity is useful for land-use planning, nature conservation and
landscape management to promote geoconservation and sustainable
development (Brilha et al., 2018; Zwoli´
nski et al., 2018), not many
studies refer to the spatial correlation between geodiversity assessment
and geosites on the basis of the concepts. As described above, in order to
have a strong teorethical background, we selected denitions of geo-
diversity, geoheritage, and geosite based on semantic and ontological
studies (see Section 3). On the basis of these denitions, aiming to
establish whether areas with the greatest geodiversity are the ones with
the most relevant geoheritage (and consequently if the geodiversity
intex map could be a useful tool to identify geosites in the area), we have
mapped the geodiversity and geosites of Alagna Valsesia and analysed
their spatial correlation in the eld. Table 1 shows the results of the data
collection. In order to assess the geodiversity of Alagna Valsesia, we
created 5 geodatabases containing the geodiversity elements of the area
in polygonal and point format. The resulted shapele including the 1069
points representing all the selected geodiversity elements is shown in
Fig. 4. In our study, the geodiversity index map corresponds to the
application of kernel density analysis; the values score between 0 and
20.56 and were divided into 5 classes of geodiversity according to Jenks
natural breaks, from very low (<0.5009) to very high (>7.1935), as can
be observed in Fig. 5.
Generally, the higher values of geodiversity are recorded in the
central and western part of the study area. In fact, the landscape of
Alagna Valsesia is exceedingly complex since there is no precise corre-
spondence between the geomorphological features and the structure
pattern, due to the multiple geomorphological processes functioning on
the area. Therefore, it seems that the regions with higher geodiversity
coincide with those where the geological exogenous processes are more
intense. Concerning the central part, the concentration of high geo-
diversity follows the main valley, where deposits and accumulation
landforms are mostly present and gravitational and uvial processes are
pronounced. The presence of a large number of geological and hydro-
logical elements is more likely to explain the high values recorded in the
western part. Conversely, low and very low geodiversity are observed in
the northern region of the research area, which is situated at the highest
elevations where predominantly only glacial and periglacial processes
are active.
Fig. 6 shows that the identication of geosites in Alagna Valsesia
resulted in the recognition of 25 geosites (also present in Table 2). Un-
like the geodiversity index, the selected geosites are approximately
evenly distributed throughout the study area. Concerning the primary
scientic interest, four interests were recognized: geomorphology (GM),
structural geology (ST), georesources (GRS), hydrology (HYD) and
geohistorical (GS). Table 3 shows that the majority of geosites are
related to geomorphological interest (68 %). Although the local study
led us to choose a small study area, it is appreciable that we recorded 3
geosites of international importance (12 %), mainly related to geore-
sources and structural geology interests, testifying to the relevant geo-
heritage and the geotouristic potential of the area. However, the most
represented importance is the regional one, comprising 48 % of the
geosites.
Consistent with previous research (Chrobak et al., 2021; Gonçalves
et al., 2022), no correlation was found between the presence of geosites
and the geodiversity index score (Fig. 6). This lack of correlation was
also observed in the aforementioned studies, despite the use of a
different method to create the geodiversity map. As can be seen in
Table 4, in Alagna Valsesia only a minimal number of geosites occurs on
the areas of high geodiversity (12 %), while the most of the geosites are
associated with areas of moderate geodiversity. Notably, no geosites are
recorded in areas characterized by a high level of geodiversity. Based on
these results, the correlation tests strongly conrmed no linear corre-
lation between the number of geosites and the class of the Geodiversity
Index. Specically, the results of the Spearman and Kendall tests are
−0.462 and −0.316, respectively (Table 5). Moreover, for both of the
tests, an alpha of 0.05 was chosen and in both cases the p-value is
signicantly higher than alpha. This means that the tests are not
Fig. 4. Illustrative procedure of the creation of the nal dataset collecting all the geodiversity elements of Alagna Valsesia. According to Forte et al. (2018), the
polygonal elements of each geodiversity unit were converted in punctual features (centroids tool) and merged together with the other punctual features in a nal
shapele containing 1069 geodiversity elements.
M. Guerini et al.
Geomorphology 461 (2024) 109298
8
signicant and it is essentially impossible to accept the null hypothesis
of a correlation.
Having acknowledged the non-linear relationship between geo-
diversity class and number of geosites, we applied numerous non-linear
regression models in RStudio in an attempt to nd the best model rep-
resenting the relationship between these variables. The evidences sug-
gest that the regression model which better represent the relation
between geodiversity class and number of geosites is the polynomial
regression model (2nd degree polynomial) (Fig. 7).
Using this model results in a correlation coefcient r
2
of 0.6454, but
the p-value is still the most important value for this test. In fact, the p-
value of 0.1773 is above the threshold alpha of 0.05 (Table 6), indicating
that the test is not signicant, as with the other tests we conducted. Our
study was unable to nd a signicant regression model describing the
relationship between geodiversity richness and geoheritage occurrence
in the eld. This conrms that there is no predictable correlation be-
tween the two variables.
6. Discussion
This study provide a comprehensive investigation of the correlation
between geoheritage and geodiversity in terms of both concepts and
eldwork. There is a gap in the literature between these two concepts
and methodologies (Crisp et al., 2021), and it is still not fully
acknowledged what the potential uses of the geodiversity map are
(Santos et al., 2017; Gray, 2021; Gonçalves et al., 2022), partly due to
the lack of a robust and unambiguous conceptual framework. As pre-
viously described (see Section 3), based on semantic and ontological
studies, in this paper geodiversity is considered according to Gray (2013;
see Mantovani, 2024), which is in good agreement with 88 % of the
researchers (Boothroyd and Henry, 2019); whereas geoheritage is
considered according to Sharples (2002) (see Mantovani, 2024),
because it does not impose restrictions on specic values and allows for
the inclusion of all other denitions, thus supporting decision makers.
These two concepts describe different features of the natural environ-
ment. Eventually, on the basis of these denitions, we can establish a
theoretical framework for understanding their relationship.
Geodiversity includes the totality of natural abiotic elements within
a given area. It is worth noting that geodiversity concept comprises a
wide range of natural elements; however, their intrinsic value is not
expressly addressed in its denition. Whereas the geosites are a
delimited areas in which signicant geodiversity elements are present,
and geoheritage is a subset of geosites that only includes features that
have a value and are considered to be of signicant importance, as
already observed by other works ( ´
Olafsd´
ottir and Dowling, 2014; Wil-
liams et al., 2020; Zakharovskyi and N´
emeth, 2021b). We were able to
consider the geosites in the eld as areas in which geoheritage occur by
linking interest and values (Diaz Martinez and Fernandez Martinez,
2015). Although these denitions make the relationship between geo-
diversity and geoheritage clear, they do not in themselves clarify their
spatial correlation. We based on these theoretical considerations to
produce the geodiversity index map of Alagna Valsesia by following a
revised version of the method proposed by Forte et al. (2018). Indeed,
this quantitative approach makes it possible to create a geodiversity map
that represents the spatial distribution and the variety of geodiversity
elements, according to the denition by Gray (see Mantovani, 2024),
avoiding to include their values, which are features of the geoheritage,
and decreasing subjectivity in the process (Fern´
andez et al., 2020).
Then, after a literature review and eld trips, 25 geosites were selected
and mapped in the same study area. By overlaying the geodiversity
index map with the geosite map no particular spatial correlation be-
tween geodiversity and geoheritage was shown. In particular, only 12 %
of the geosites are located in areas of high geodiversity and none in areas
of very high geodiversity. This result shows that some geosites may
occur in areas of low geodiversity. Specically, this study nds that, in
the eld, the geoheritage occurrence increase only up to the “moderate
geodiversity” class, while then the number of geosites decreases as the
geodiversity class increases. However, given the signicant difference of
Fig. 5. Quantitative geodiversity index map of the municipality of Alagna Valsesia. The lithology, geomorphology, soil, hydrography and quarry and mine data were
considered to produce this map by applying the kernel density function (Forte et al., 2018). The geodiversity classes have been divided according Jenks Natural break
(Jenks, 1967).
M. Guerini et al.
Geomorphology 461 (2024) 109298
9
Fig. 6. Overlay of the geosites map with the geodiversity index map in Alagna Valsesia. In green are the “very low geodiversity” class areas, in red “very high
geodiversity”.
Table 2
List and location of selected geosites in Alagna Valsesia. Primary interests: structural geology (ST), georesources (GRS), hydrology (HYD), geomorphology (GM),
Geohistorical (GS). Importance: International (I), national (N), regional (R), local (L). The geodiversity index indicates the value of quantitative geodiversity at the
location of the geosite.
Geosite Primary interest Importance Latitude (N) Longitude (E) Geodiversity Index
Stolemberg ST I 45.867 7.866 1.25
Alpe stofful GRS R 45.867 7.918 0.49
Flua I glacier GM R 45.916 7.921 0.74
Acquabianca waterfall GM L 45.885 7.933 1.67
Locce sud glacier GM R 45.920 7.912 0.01
Pisse waterfall GM L 45.882 7.893 2.56
Sesia-Vigne glacier GM R 45.918 7.891 0.02
Sesia kettle GM L 45.884 7.25 2.97
Piode glacier GM R 45.907 7.878 0.96
Sesia springs HYD R 45.905 7.905 1.52
Flua glacier GM R 45.916 7.927 1.50
Parrot glacier GM R 45.914 7.883 1.88
Bors glacier GM R 45.896 7.870 0.97
Otro glacier GM R 45.826 7.883 1.30
Cimalegna plateau GM N 45.874 7.876 1.18
Fondecco Moraine GM R 45.867 7.918 1.66
Pulfer stein GM L 45.850 7.937 2.46
Otro valley GS R 45.843 7.915 0.95
Golden mine (Kreas) GRS I 45.874 7.936 4.99
Golden mine (S. Maurizio) GRS I 45.889 7.912 4.24
Manganese mine GRS L 45.846 7.926 2.54
“Bocchetta” of Pisse GRS L 45.877 7.901 3.97
Alpe Pile GM L 45.884 7.927 2.15
Bors Plain GM L 45.888 7.909 3.49
Otro kettle GM L 45.847 7.935 2.55
M. Guerini et al.
Geomorphology 461 (2024) 109298
10
geosites number in the ve geodiversity classes, even when taking into
account that “high geodiversity” and “very high geodiversity” classes are
less widespread than the other classes, it is not possible to admit that
there is a spatial correlation between geodiversity and geoheritage. This
is particularly true for the results of the correlation tests.
The two correlation tests applied, the Kendall and Spearman ones,
show no spatial linear correlation between the variables “geodiversity
class” and “number of geosites”. In particular, the correlation
coefcients of the Spearman and Kendall tests are −0.462 and −0.316,
respectively, with a p-value that is much higher than the alpha (0.05) in
both cases. Indeed, it was already clear from the scatterplot (Fig. 7) that
there is no clear monotonic relationship between the two variables,
neither negative nor positive, rendering the two tests void of signi-
cance. Hence, our study shows that in Alagna Valsesia the areas with the
greatest geodiversity are not the ones with the most relevant geo-
heritage. Notably, this result is in accord with previous studies that show
that areas of high geodiversity are not necessarily related to the presence
of geosites, while areas of low geodiversity may contain sites of
geological interest (Brocx and Semeniuk, 2007; Santos et al., 2017;
Chrobak et al., 2021; Gray, 2021; Gonçalves et al., 2022), but our work
conrms this in an innovative way, with eldwork based on a semantic
and ontological study of denitions (Mantovani and Lombardo, 2022).
Furthermore, even all other non-parametric regression models tested
were not signicant, indicating that there is no predictable relationship
between geodiversity and geoheritage in our study area. This eld result
is crucial because it imply that the geodiversity index map, created with
the quantitative methods, could not be a useful tool for geosites recog-
nition and tourism promotion. Indeed, geodiversity and geoheritage are
different features of the abiotic environment (Gray, 2019), and for this
reason the methodologies used to assess geodiversity and to perform a
geological inventory are different (Gonçalves et al., 2022). Moreover,
this supports the idea that any environmental management focused on
geoconservation and geotourism planning requires the recognition of
what can be considered geoheritage in the area, that is, the selection,
mapping and promotion of the geosites (Brilha, 2018; Selmi et al., 2019;
Crofts et al., 2020), while the quantitative geodiversity map could be
only a complementary tool.
However, the knowledge of geodiversity is the backbone of geo-
heritage (as the geoheritage are elements of the geodiversity with a
particular value) and of geoconservation (Gray, 2018). Previous studies
have shown that different approaches give different results (Gonçalves
et al., 2022), and the relationship between geodiversity and geoheritage
is usually shown in geodiversity assessment studies using a qualitative
approach (Brilha et al., 2018). Thus, the qualitative map becomes a
useful tool for recognition (Zakharovskyi et al., 2023) and management
(Najwer et al., 2023) of geosites. Nevertheless, qualitative maps can
have some drawbacks: this approach involves assigning numerical
values to geodiversity elements based on their qualitative value, which
introduces a degree of subjectivity into the process (Crisp et al., 2021).
Although this makes it more functional for certain purposes, there is a
risk that it moves away from the denition of geodiversity, which only
includes the diversity of elements and not their values, which is what
geoheritage is all about. In addition, the results of this work are in
support of previous research that has shown that recognition of geo-
heritage is somewhat subjective (Fern´
andez et al., 2020). In fact, the
selection of geoheritage in the past may have been based on criteria that
favored cultural aspects (e.g., common wisdom of local communities)
over scientic ones, and for this reason spatial correlation may not
occur. Therefore, there is a clear need to rationalize indicators and
values that would allow the attribution of geoheritage status to geo-
diversity elements (Pereira et al., 2010).
Nonetheless, as highlighted in earlier research (Hjort and Luoto,
Table 3
Percentages of selected geosites in Alagna Valsesia divided by type of interest
and importance. Type of interests: structural geology (ST), georesources (GRS),
hydrology (HYD), geomorphology (GM). Importance: International (I), national
(N), regional (R), local (L).
Type of
interest
Number of
geosites
% Level of
importance
Number of
geosites
%
GM 17 68 I 3 14
GRS 5 20 N 1 9
HYD 1 4 R 12 48
ST 1 4 L 9 29
GS 1 4
Table 4
Number and percentage of geosites occurring on the areas of the different geo-
diversity classes in Alagna Valsesia. geodiversity classes were calculated using a
quantitative method (Forte et al., 2018) and range from very low to very high.
Geosites were identied through literature review and eldwork.
Geodiversity class Number of geosites Geosites %
Very Low 3 12
Low 8 32
Moderate 11 44
High 3 12
Very high 0 0
Table 5
Results of the correlation tests applied during the eldwork in Alagna Valsesia.
The considered variables were “number of geosites” and “geodiversity class”.
Type of value Kendall test Spearman test
Correlation coefcient −0.316 −0.462
Parameters Z =-0.758 S =29
P-value 0.449 0.434
Fig. 7. Result of the second-degree polynomial regression model. This model
resulted as the more accurate for describing the spatial relationship between
geodiversity class and number of geosite in Alagna Valsesia; but the p-value
higher than the alpha threshold makes the test not statistically signicant
proving that in our case study area there is not predictable spatial relationship
between these two variables.
Table 6
Statistical results of the application of the second-degree
polynomial model between the variables geodiversity
class and geosites number in Alagna Valsesia.
Type of value values
Degree 2nd
Residual standard error 2.63
Multiple r
2
0.8227
Adjusted r
2
0.6454
f-statistic 4.64
p-value 0.1773
M. Guerini et al.
Geomorphology 461 (2024) 109298
11
2010; Santos et al., 2017), the quantitative geodiversity map provides a
direct and effective approach to evaluate the richness of the physical
environment. Therefore, this method may be helpful in other scenarios,
such as identifying abiotic ecosystems and the ways that geodiversity
affects biodiversity. Previous studies comparing geodiversity and
biodiversity have shown that they are distinct elements of the natural
environment: both are capable of providing services to humans, and
together, they make up all the elements of the natural environment
(Gray, 2019; Frisk et al., 2022; Herrera-Franco et al., 2022). Neverthe-
less, although geodiversity–biodiversity relationship can be very com-
plex and still needs more evidence (Alahuhta et al., 2019), it is now
acknowledged that geodiversity can affect and underpin biodiversity
(Tukiainen et al., 2017a; Ren et al., 2021). Particularly, geodiversity and
biodiversity relationships have been demonstrated by highlighting the
signicant inuence of abiotic heterogeneity on habitat richness
(Jaˇ
ckov´
a and Romportl, 2012), vegetation (dos Santos et al., 2019),
species richness (Salminen et al., 2023), and presence of ecosystem
services (Alahuhta et al., 2018; Garcia, 2019; Queiroz and Garcia, 2022).
Thus, the quantitative geodiversity map could be important in providing
more information about a landscape's potential for biodiversity con-
servation (Anderson and Ferree, 2010; Lawler et al., 2015), and it would
be considered an important tool in dening protected areas (Tukiainen
et al., 2017b; Fern´
andez et al., 2020). Therefore, the quantitative geo-
diversity map can be a useful surrogate of biodiversity, and should be
incorporated into biodiversity research and conservation (Hjort et al.,
2012; Lawler et al., 2015). Furthermore, climate change is another
important factor that can impact the geodiversity and the geosites, thus
impacting both the biodiversity and the services the geodiversity pro-
vides to humans (Gordon et al., 2022).
7. Conclusions
This study aimed to investigate the relationship between the geo-
diversity richness and the presence of geoheritage in Alagna Valsesia
(Sesia Val Grande UNESCO Global Geopark, Italian Western Alps), dis-
cussing whether the areas with the greatest geodiversity are the ones
with the most relevant geoheritage, thus questioning the potential use of
the geodiversity index map. Upon a strong theoretical framework based
on semantic and ontological studies, by using the geosites and the
quantitative geodiversity index maps, our study showed that there is no
spatial correlation between the geodiversity class and the number of
geosites, proving that some geosites may occur in areas of low geo-
diversity, and the greatest geodiversity areas are not the ones with the
most relevant geoheritage. An accurate statistical analysis conrmed
this result: the Kendall and Spearman correlation tests showed the
impossibility to admit the correlation between the geodiversity richness
and the geoheritage occurrence in the eld. Moreover, all the other non-
parametric regression models tested were not signicant, indicating that
there is no predictable relationship between geodiversity and geo-
heritage in our study area. For that reason, the quantitative geodiversity
map could not be a useful tool for geosites recognition and tourism
promotion, while for this purpose should be better use a qualitative
geodiversity map. However, the potential use of quantitative geo-
diversity map was discussed highlighting its role for geoconservation
and the strong inuence of geodiversity on biodiversity. Finally, the
potential use of the geodiversity map depends on the study's purpose and
the approach used to produce it. As previously noted (Gonçalves et al.,
2022), the two approaches may be complementary. It is recommended
that future studies focus on applying these approaches in a comple-
mentary manner to develop land management that considers both the
inuence of geodiversity on biodiversity and the signicance of geo-
conservation and geotourism promotion.
Data availability statement
Data available via the Zenodo Digital Repository doi:https://doi.
org/10.5281/zenodo.10636050 (Guerini et al., 2024).
CRediT authorship contribution statement
Michele Guerini: Writing – review & editing, Writing – original
draft, Visualization, Validation, Supervision, Software, Resources,
Methodology, Investigation, Formal analysis, Data curation, Conceptu-
alization. Alizia Mantovani: Writing – review & editing, Writing –
original draft, Validation, Resources, Methodology, Investigation, Data
curation, Conceptualization. Rasool Bux Khoso: Visualization, Re-
sources, Data curation. Marco Giardino: Writing – review & editing,
Writing – original draft, Validation, Supervision, Resources, Funding
acquisition.
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.
Acknowledgements
The authors thank the entire staff of the Sesia Val Grande UNESCO
Global Geopark and of the Monterosa2000 s.p.a. for the support during
the eld trips and the data collection. The authors also thank the Mu-
nicipality of Alagna Valsesia in the person of the mayor Roberto Veggi
for the fruitful cooperation, especially during the phase of data collec-
tion. Finally, the authors thank the three reviewers. This study was
funded by the European Commission Horizon 2020 ArcticHubs-project
(Global drivers, local consequences: Tools for global change adapta-
tion and sustainable development of industrial and cultural Arctic
“hubs”) - Grant Agreement No 869580.
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