Post on 03-Aug-2020
transcript
RESEARCH ARTICLE
Integrating supply and demand in ecosystem service bundlescharacterization across Mediterranean transformedlandscapes
Cristina Quintas-Soriano . Marina Garcıa-Llorente . Albert Norstrom .
Megan Meacham . Garry Peterson . Antonio J. Castro
Received: 4 March 2018 / Accepted: 20 April 2019
� Springer Nature B.V. 2019
Abstract
Context Humans continually transform landscapes,
affecting the ecosystem services (ES) they provide.
Thus, the spatial relationships among services vary
across landscapes. Managers and decision makers
have access to a variety of tools for mapping
landscapes and analyzing their capacity to provide
multiple ES.
Objectives This paper characterizes and maps ES
bundles across transformed landscapes in southeast
Spain incorporating both the ecological and social
perspectives. Our specific goals were to: (1) quantify
ES biophysical supply, (2) identify public awareness,
(3) map ES bundles, and (4) characterize types of ES
bundles based on their social-ecological dimensions.
Methods Biophysical models and face-to-face social
surveys were used to quantify and map ES bundles and
explore the public awareness in a highly transformed
Mediterranean region. Then, we classified ES bundles
into four types using a matrix crossing the degree of
biophysical ES supply and the degree of social
awareness.
Results Results mapped seven ES bundles types
representing diverse social-ecological dynamics. ES
Electronic supplementary material The online version ofthis article (https://doi.org/10.1007/s10980-019-00826-7) con-tains supplementary material, which is available to authorizedusers.
C. Quintas-Soriano (&)
Social-Ecological Interactions in Agricultural Systems
Lab, Faculty of Organic Agricultural Sciences, University
of Kassel, Steinstraße 19, 37213 Witzenhausen, Germany
e-mail: cristina.quintas@uni-kassel.de
C. Quintas-Soriano � A. J. CastroBiology and Geology Department, Andalusian Center for
the Assessment and Monitoring of Global Change
(CAESCG), University of Almeria, 04120 Almerıa, Spain
e-mail: acastro@ual.es
C. Quintas-Soriano
FRACTAL Association, San Remigio 2, 28022 Madrid,
Spain
M. Garcıa-Llorente
Social-Ecological Systems Laboratory, Department of
Ecology, Universidad Autonoma de Madrid,
28049 Madrid, Spain
e-mail: marinaglloren@gmail.com
M. Garcıa-Llorente
Applied Research and Agricultural Extension Department,
Madrid Institute for Rural, Agricultural and Food
Research and Development (IMIDRA), Finca
Experimental el Encın, 28800 Alcala De Henares, Madrid,
Spain
A. Norstrom � M. Meacham � G. PetersonStockholm Resilience Center, Stockholm University,
Kraftriket 2B, SE-10691 Stockholm, Sweden
e-mail: albert.norstrom@su.se
123
Landscape Ecol
https://doi.org/10.1007/s10980-019-00826-7(0123456789().,-volV)( 0123456789().,-volV)
bundles mapped at the municipality level showed
mismatches between their biophysical provision and
the public awareness, which has important implica-
tions for operationalizing the bundles concept for
landscape planning and management. ES bundles
characterization identified four types of bundles
scenarios.
Conclusions We propose an ES bundles classifica-
tion that incorporates both their social and ecological
dimensions. Our findings can be used by land man-
agers to identify areas in which ES are declining as
well as priority areas for maximizing ES provision and
can help to identify conflicts associated with new
management and planning practices.
Keywords Dryland � Public awareness � Spain �Social-ecological system � Synergy � Trade-off
Introduction
Humans have transformed most of the Earth’s land
surface (Foley et al. 2005; Ellis 2011). While these
land transformations vary from place to place, their
effect has become a major driver of change at the
global scale. One major consequence is the spatial
shifts in both the supply of ecosystem services (i.e.,
benefits that people obtain from ecosystems) and the
beneficiaries of those services (Eigenbrod et al. 2011;
Castro et al. 2018a). For example, as more of the
Earth’s surface is converted into simplified and
intensive production landscapes there is a growing
spatial disconnect between the location of crop
production and where it is consumed (D’Odorico
et al. 2014; MacDonald et al. 2015). In the Mediter-
ranean region, the major land transformations are
urbanization, agriculture intensification, and rapid
changes in tourism activities and developments (Ni-
eto-Romero et al. 2014; Vigl et al. 2017). These
transformations have produced trade-offs among
ecosystem services [e.g., intensive agriculture pro-
duction from greenhouses and water supply coming
from groundwater and aquifer recharge (Quintas-
Soriano et al. 2014)], which result in conflicts among
stakeholder groups across different landscapes. The
concept of ecosystem services (ES) has been adopted
by managers and policy-makers worldwide as a way to
communicate the dependence of human well-being on
the benefits ES (Bastian et al. 2012). Nowadays,
managers and decision makers have access to a variety
of tools for mapping multiple ES or ecosystem service
bundles (Bennett et al. 2009; Balvanera et al. 2017).
The analysis of ES bundles across landscapes allows
for the inclusion and visualization of multiple ES
simultaneously, reflecting the multifunctionality of
landscapes and reducing the risk of policy failure by
focusing on inherently synergistic bundles of ES,
rather than individual ES (Turkelboom et al. 2018).
The concept of ES bundles emerged as one way to
understand relationships among multiple ES, in order
to avoid unwanted trade-offs and take advantage of
synergies between these services (Bennett et al. 2009).
The first quantitative studies of ES bundles defined
them as a set of ES that repeatedly appear together
across space or time (Raudsepp-Hearne et al. 2010).
Since then, several studies have used this biophysical
and spatio-temporal definition and identified ES
bundles in different landscapes (e.g., Maes et al.
2012; Turner et al. 2014; Crouzat et al. 2015; Derkzen
et al. 2015; Renard et al. 2015; Queiroz et al. 2015;
Yang et al. 2015). A second, and more recent,
approach to identify ES bundles has focused on the
socio-economic dimensions that can mediate relation-
ships between different ES (Plieninger et al. 2013;
Hicks and Cinner 2014). For example, Martın-Lopez
et al. (2012) explored the characterization of ES
bundles in Spain by assessing the socio-cultural
preferences of different stakeholder groups toward
different ES. Similarly, Hamann et al. (2015) used
national census data on the direct use of six provi-
sioning services to map ES bundles across South
Africa. However, despite this progress only one
previous study has evaluated ES bundles from a
supply–demand perspective (Baro et al. 2017) and no
study has simultaneously assessed and related the
biophysical and social dimensions of ES bundles in a
given landscape using social perceptions. A better
understanding of how ES bundle dynamics are
M. Meacham
e-mail: megan.meacham@su.se
G. Peterson
e-mail: garry.peterson@su.se
A. J. Castro
Social-Ecological Research Laboratory, Department of
Biological Sciences, Idaho State University, Pocatello,
ID 83209, USA
123
Landscape Ecol
influenced by the biophysical, ecological and social
components over space and time will improve our
ability to manage ES sustainably (Bennett et al. 2015).
For example, identifying spatial mismatches between
areas of ES bundle supply and demand—e.g., along
rural–urban gradients—can help guide decision mak-
ers on which areas need special conservation strategies
and at what institutional scales ES need to be
managed.
This paper characterizes and maps ES bundles
across transformed landscapes in southeast Spain by
incorporating both ecological and social dimensions.
Our specific goals are to: (i) quantify the ES biophys-
ical supply by examining ES diversity patterns and
mapping hot and cold spots of ES, (ii) identify the
public awareness by exploring the social importance
regarding ES, (iii) characterize and map ES bundles,
their synergies and mismatches using both the eco-
logical and social dimension, and (iv) classify types of
ES bundles based on their social-ecological
dimensions.
Methods
Study area
Spanish semi-arid ecosystems are among the driest
regions in continental Europe and have experienced
different types of land use transformations (Armas
et al. 2011). The most dramatic and well-known land
use change has been the rapid transition toward
intensive greenhouse horticulture, hosting the largest
concentration of greenhouses in the world (approx.
26,750 ha), also known as, ‘‘The Plastic Sea of
Almerıa’’ (Aznar-Sanchez et al. 2011) (Fig. 1a). This
specific transformation has been linked to severe
ecological, economic and socio-cultural consequences
(Aznar-Sanchez et al. 2011; Munoz-Rojas et al. 2011;
Requena-Mullor et al. 2018). Additionally, the main
job source in the area is the agribusiness sector, so the
population growth due to agriculture expansion has
promoted urban expansion and is accompanied by
massive tourism along the coast. However, this region
has also witnessed a large increase in the number and
size of protected areas (from 4% of the surface in 1980
to 20% in 2016) (Quintas-Soriano et al. 2016; Castro
et al. 2018b).
Ecosystem services mapping
Seven ES were spatially quantified and mapped,
including both intermediate and final services (Fisher
et al. 2009). Intermediate ES are the result of complex
interactions between ecosystem structure and pro-
cesses (e.g., water recharged by aquifers). Final ES
(e.g., food production) are produced from the combi-
nation of intermediate ES with other forms of capital
to provide benefits to human welfare (Castro et al.
2015). Intermediate ES included climate regulation,
water regulation, soil protection and habitat quality,
and final ES were food from traditional agriculture,
food from intensive agriculture and tourism. ES were
selected based on their importance in the study area,
data availability and their implication for the welfare
of local communities (Garcıa-Llorente et al. 2012;
Castro et al. 2014, 2015; Quintas-Soriano et al.
2014, 2016; Requena-Mullor et al. 2018). Table 1
and Online Appendix A summarizes the indicators,
data sources and models used to measure the ES.
Social perceptions of ecosystem services
The social importance of six ES was assessed by
conducting face-to-face surveys across the study area.
To test the suitability of the questionnaire design, we
conducted a preliminary survey in the study area
(Martın-Lopez et al. 2012; Castro et al. 2016a). We
randomly interviewed local respondents in the streets
compiling a total of 441 face-to-face valid question-
naires in 2012 at 26 sampling sites across the study
area (Fig. 1b). Individuals were sampled from the
population to encompass a wide range of the local
citizenry (e.g., residents, environmental experts, or
business workers) (Castro et al. 2016b). The sampling
frame was restricted to individuals over 18 years old.
We had no contact with any of the respondents prior to
the survey. The questionnaires included information
regarding: (1) respondent’s relationship with the study
area, (2) respondent’s perception of the importance of
ES for human well-being, (3) respondent’s perception
toward land use types, and (4) respondent’s general
environmental awareness as well as socio-demo-
graphic information. In this study, we used the data
of the second section to evaluate how local public
perceived the importance of ES. Respondent were also
asked to select the four most important ES from a total
of eight ES previously determined as important for the
123
Landscape Ecol
local public in the study area: traditional agriculture,
intensive agriculture, climate regulation, air quality,
water regulation, soil protection, tourism and local
identity (Online Appendix B). We estimated the
importance perceived for a given ES as the number
of respondents that selected that service as one of their
four most important ES. For this study, we only
employed the data for those services that were also
mapped with the biophysical models. Habitat quality
was not included in the survey because it was not
initially selected as an important service for the local
public in the study area.
Spatial scale and data analysis
ES delivery was assessed at the municipality level,
because this represents the smallest administrative
boundary for land management in Spain (Raudsepp-
Hearne et al. 2010; Queiroz et al. 2015). The case
study included 160 municipalities with a median size
of 75.48 km2, and that ranged in size from 1.5 to
600 km2 (See Fig. 1) (Quintas-Soriano et al. 2014;
Requena-Mullor et al. 2018). ES supply was first
averaged and standardized by the total area of each
municipality and then normalized to enable compar-
ison (Castro et al. 2014, 2015). The diversity of ES
present in each municipality was assessed using the
Simpson’s index (Oksanen et al. 2018). Each ecosys-
tem service value was normalized to be between 0 and
1 and each ES was given equal weight. Each
municipality was assessed using the same set of
ecosystem services. The Simpson’s index is a measure
of evenness and calculates where there is a more even
presence of all the ES verses where a municipality is
Fig. 1 Location of the case study delimiting the arid and semi-
arid ecosystems of Iberian Peninsula: a land use types
represented with different colors across 160 municipalities,
b population density across municipalities and sampling points
of the survey. Areas excluded within the study area boundaries
correspond with the highest mountain ranges that are not arid
and semi-arid ecosystems
123
Landscape Ecol
dominated by only one or a few ES. A municipality
supplying multiple ES would score higher than a
municipality only considered to provide habitat, for
example. Higher values indicate a more diverse set of
ES present in that municipality.We categorized the ES
into two categories, final ES and intermediate ES. We
then calculated the average supply of these two
categories of ES across all the municipalities. We
calculated the average supply of the two categories of
ES for the region as a whole and mapped each
municipalities’ residual from the regional average.
These residuals represent ‘‘hot’’ (higher production)
and ‘‘cold’’ (lower production) spots. Interactions
among ES were analyzed using a principal component
analysis (PCA) and cluster analysis. PCA identified
the main explanatory factors of the variability and
distribution of the ES across the municipalities.
Cluster analysis identified groups of municipalities
with similar provision levels of ES, or ecosystem
service bundle types. K-means clustering was used to
identify distinct types of bundles and the selection of
the number of clusters was based on cluster robustness
and knowledge of the social-ecological system (Raud-
sepp-Hearne et al. 2010; Queiroz et al. 2015). We used
flower diagrams to visualize biophysical ES bundles.
All bundles were calculated from normalized values
obtained for each service, and the area of flower petals
represents ES supply.
We determined the percentage of respondents who
valued the social importance for each ES, estimating
the number of respondents who chose each ES as
important. In addition, we estimated the social
importance for each ES within each bundle by
calculating the average value for the set of munici-
palities included in each bundle. This information is
presented using flower diagrams for each bundle.
Finally, following Iniesta-Arandia et al. (2014), we
classified ES bundles into four types using a matrix
crossing the degree of biophysical ES supply and the
degree of social awareness. We expressed values for
each bundle using scatter plots for final and interme-
diate ES categories. We calculated the median of each
axis and used it as the cut values to decide which ES
bundles were perceived as highly important or having
Table 1 List of ecosystem services assessed, indicators and units
Ecosystem services
classification
Ecosystem
service type
Biophysical indicator or proxy Measure units Data source
Provisioning
Food from traditional
agriculture
Final Food production from traditional
agriculture practices
Tm/ha per year Statistical data from
Spanish department of
agriculture
Food from intensive
agriculture
Final Food production from greenhouses Tm/ha per year Statistical data from
Spanish department of
agriculture
Regulating
Climate regulation Intermediate Carbon sequestration Tm/ha per year InVEST, carbon
sequestration: climate
regulation model
Soil protection Intermediate Capacity of vegetation cover to soil
conservation and to avoid soil erosion
Tm/ha per year Andalusian department of
environment. USLE soil
equation
Water regulation Intermediate Groundwater recharge and water
supplied by reservoirs
hm3/ha per year APLIS model
Habitat quality Intermediate Spatial extent and quality of habitat for
the conservation of biodiversity
km2 InVEST, habitat quality
model
Cultural
Tourism Final Number of annual person-days of
photographs uploaded to the photo-
sharing website flickr
km2 InVEST, visitation:
recreation and tourism
model
123
Landscape Ecol
high biophysical supply. We used QGIS 2.12.1 to map
the spatial distribution of ES and R to conduct all
spatial analysis and produce all the figures (R Core
Team 2018).
Results
Ecosystem service supply
The provision of each ES showed distinct spatial
patterns across the study area (Fig. 2). Food produc-
tion from cultivated crops (both intensive and tradi-
tional agriculture) was delivered in distinct areas.
Food production from traditional agriculture (i.e., non-
greenhouse agriculture) was distributed in more
central and northern areas characterized by higher
altitude, irregular surfaces and slopes, corresponding
with household and small-scale agricultural activities
(called ‘‘minifundios’’). Food from intensive agricul-
ture (i.e., greenhouses) was mainly produced in
southern flat areas. Intermediate ES supply had a
markedly different spatial pattern. Climate regulation
was distributed extensively across the study area,
exhibiting the highest values in the south-west area. In
contrast, soil protection was mainly located in the
south-west, overlapping with the maximum values of
climate regulation. Maximum water regulation values
were located in the southwest and northwest parts of
the study area, in areas where recharge is promoted
and aquifers are located, whereas the southeast areas
offered the lowest values. Habitat quality presents
higher values in internal areas, concentrated in areas
with low population density. Finally, tourism was
primarily located in the more densely populated
municipalities along the coast (Fig. 2; See Online
Appendix A).
We found differences between the average ES
supply and distributions of hot and cold spots for final
and intermediate ES. Final and intermediate ES
showed opposite distributions (Fig. 3a, b). Final ES
were mainly located in the south coastal municipalities
(distributed in 45 municipalities). Hot spots of final ES
covered urban municipalities in coastal areas that are
Fig. 2 Distribution of the values obtained for individual ecosystem services across 160 municipalities in the study area. Darker shades
of blue represent a higher provision of the service. (Color figure online)
123
Landscape Ecol
densely populated and contain intensive agriculture
production. Conversely, intermediate ES covered a
greater number of municipalities (88 municipalities),
excluding most of the coastal municipalities. Hot spots
of intermediate ES were mainly located in the northern
and southwest areas. Most municipalities showed
varied sets of ES with high values of diversity across
the entire region (Fig. 3c). The lowest values of ES
diversity were mainly located in the north, corre-
sponding with the lowest values of food from tradi-
tional agriculture, as well as the densely populated
coastal municipalities. The highest values tended to be
located in municipalities in southern and eastern
coastal areas. Most of these municipalities presented
low population density and hot spots of intermediate
services.
Respondents and perceptions of ecosystem service
importance
The respondents (n = 441) reflected the average
characteristics of the local population for our study
site in terms of age, education, income, and gender
(See Online Appendix C). A slightly larger proportion
of men were surveyed (54.88% of male respondents
vs. 45.12% of women respondents). The vast majority
of respondents interviewed were local residents
(78.68%), while 21.32% constituted expert respon-
dents. 75% of respondents were younger than
50 years. Most of the respondents showed a high
level of education (42.63% with a university degree)
and mid-low levels of income (68.75% of respondents
with an income lower than 1500 euros per month).
Almost 30% of respondents had professional jobs
(e.g., science and engineering professionals, health
professionals, teaching professionals or business and
Fig. 3 a Average supply, b hot and cold spots, and c diversityvalue of ES across 160 municipalities. Services diversity was
calculated by a derivation of the original Simpson’s diversity
index. Hot spots (represented by an increasing gradient of red)
are municipalities with a high delivery of a given type of service
relative to the region as a whole, while cold spots (represented
by a decreasing gradient of blue) are municipalities where the
delivery of a given type of service is relatively low. (Color
figure online)
123
Landscape Ecol
administration professionals) and almost 20% of them
had a job in the service and sales sector. 30% of
respondents exhibited a more localized sense of place,
indicating a primary affinity for their own city and
regional areas (25.4% and 39.23% respectively),
whereas 26.53% reported a sense of place correspond-
ing to the national scale. Finally, proactive environ-
mental behavior (measured by membership in an
environmental association) was low (3.7%), but
respondents indicated that they usually visit natural
protected areas (81.63%) (Online Appendix C).
Overall, respondents identified final ES (i.e.,
tourism and traditional agriculture) as the most
important services for human well-being in the study
area (Fig. 4). Tourism was the ES considered by the
local public as the most important (74. 83% respon-
dents chose it from the ES panel; Online Appendix B)
followed by traditional agriculture (61.90%). Respon-
dents recognized intermediate ES (e.g., water regula-
tion and climate regulation) with a medium level of
importance (44.90% and 44.67% of respondents
respectively). A smaller number of respondents
selected intensive agriculture and soil protection
services (41.50% and 35.60% respectively), indicating
that they were considered less important by the public.
Ecosystem service bundles
The PCA analysis identified two gradients that
explained the variation of ES across the study area
(Online Appendix D). The first PCA component
explained 28% of the variance and corresponds to a
gradient of population density, from high to low, and
with a gradient of altitude, from low-lying coastal
areas to more mountainous-forest inland areas with
higher altitudes. Coastal areas are urban and have a
higher population density, while inland areas are more
rural and have less populated municipalities. The
second PCA component, 23% of the variance, corre-
sponds to a gradient from urban and agricultural areas
describing areas supplying final services, to more
natural areas with a greater supply of intermediate
services. Cluster analysis grouped the 160 municipal-
ities into seven groups of ES bundles (Fig. 5). The
number of municipalities present in each group varied
from 4 to 64. We named these bundle groups based
upon the dominant ES and land cover.
Traditional mosaic croplands (bundle 1, n = 14
municipalities; Fig. 5) grouped traditional agricultural
areas where is located crops with the highest annual
yield (See Figure A2 in Online Appendix A). Within
this bundle medium levels of other final ES (e.g.,
intensive agriculture and tourism) were supplied.
Tourism, soil protection and climate regulation were
perceived with high levels of importance, while
intensive agriculture was perceived as the least
important service. Urban touristic areas (bundle 2,
n = 5 municipalities) corresponded with highly pop-
ulated urban municipalities and with more recreational
opportunities related to beach and coastal tourism.
Within this bundle, tourism and intensive agriculture
were considered as the most important ES by locals.
Fig. 4 Level of importance
perceived towards
ecosystem services across
the study area given by
locals’ respondents
123
Landscape Ecol
Balanced multifunctional areas (bundle 3, n = 5
municipalities) grouped medium values of supply of
intermediate ES and higher values of social percep-
tions toward final ES (tourism and traditional agricul-
ture). Climate regulating areas (bundle 4, n = 13
municipalities) grouped municipalities with high val-
ues of intermediate ES supply, especially climate
regulation. Final ES exhibited low supply levels in this
bundle, and low-levels of perceived importance.
Habitat and water regulation conservation areas
(bundle 5, n = 21 municipalities) covered scrub-
grassland, forest and mosaic areas with agricultural
lands corresponding with regions with high average
altitude. These areas exhibited high levels of interme-
diate ES supply. We have no information regarding
the perceived values of the ES in this bundle because
no survey respondents inhabitant municipalities
within this bundle. Greenhouses production (bundle
6, n = 4 municipalities) covered municipalities with
greenhouses, specifically located in the ‘‘Campo de
Dalıas’’ (Fig. 5). This area is located in a coastal
platform with low altitude and above the ‘‘Sierra de
Gador’’ aquifer that allow the provision of water for
the production of horticulture. Respondents associated
with this bundle recognized intensive agriculture and
tourism as the most important ES. Soil protection was
generally perceived as not important.Habitat quality
areas (bundle 7, n = 64 municipalities) included
municipalities in depopulated rural areas covering
scrublands, forest and agricultural areas, with high
level of habitat quality, and medium levels of others
intermediate ES. Traditional agriculture and tourism
were considered as the most important ES, while
intensive agriculture as the least important service.
Ecosystem service bundles characterization:
matches and mismatches between the supply
and demand
ES bundles were characterized using their biophysical
supply level and public awareness (i.e., social impor-
tance) (Fig. 6). The characterization distinguished
between final and intermediate ES. We identified four
types of bundles configurations: (1) coupled bundles
as those with a high level of ES supply and ES public
awareness, (2) bundle mismatch type A as bundles
Fig. 5 ES bundles identified by k-means clustering for the
study area. N is the number of municipalities grouped in each
bundle. Flower diagrams show the biophysical supply and social
perceptions (importance perceived) for each ecosystem service
within each bundle. The flower diagrams are dimensionless, as
they are based on normalized data for each service, and a higher
surface area of a petal indicates the higher production and
perception of a particular service. Flower diagrams are
comparable among bundles inside biophysical supply or
importance perceived, but not between them
123
Landscape Ecol
with a high supply level but low public awareness, (3)
bundle mismatch type B as bundles with high public
awareness and low levels of ES supply, and (4) bundle
mismatch type C as bundles with low levels of both
public awareness and supply level (Fig. 6). Two
bundles were identified as coupled bundles for both
supply and demand of ES (i.e., bundle 2 for final ES
and bundle 1 for intermediate ES). However, most
bundles were identified in the quadrant describing the
mismatch type A (i.e., high levels of biophysical
supply but a low level of public awareness): bundles 1
and 6 for final ES, and bundles 2, 3, 4 and 7 for
intermediate ES. Only final ES bundles were identified
as mismatch type B (i.e., bundles 4 and 7 for final ES).
These areas indicate low values of biophysical supply
and high values of social awareness. Finally, bundle
mismatch type C, indicating low levels of both public
awareness and supply level, were found for bundle 3
for final ES, and bundle 6 for intermediate ES. It is
important to note that no data was collected about ES
social importance in bundle 5 (for both final and
intermediate ES). This bundle is defined only with
ecological data, with a high supply of habitat quality
and water regulation services, thereby it’s not possible
to develop a bundle characterization.
Discussion
Understanding the spatial distribution of ES bundles
across transformed landscapes is critical for the
success of landscape management and planning
(Opdam 2013). This study offers a comprehensive
approach for understanding the distribution of ES
bundles, including both the social and biophysical
factors that shape them. Our approach illustrates both
which ES are more or less abundant across specific
landscapes, as well as the level of public awareness
across municipalities. This combination defines the
social-ecological context that managers need to
incorporate into land decision-making.
Spatial distribution and ecosystem service bundles
characteristics
Spatially explicit mapping exercises are considered
one of the tools for ES planning and implementation in
decision-making (Goldstein et al. 2012; Bateman et al.
2013). This study proposes an analysis of ES bundles
and characterization incorporating the biophysical
factors that defines their supply as well as the public
awareness across administrative boundaries. Different
patterns were identified based on the spatial distribu-
tion of ES categories. For instance, final services (i.e.,
food from intensive agriculture, food from traditional
agriculture and tourism) were mainly localized in
municipalities along the coastline, whereas interme-
diate services (i.e., water regulation or carbon seques-
tration) were scattered across inland municipalities
(Fig. 2). The spatial supply of final and intermediate
ES was also identified by the ES hot and cold spots
analysis. The supply of intermediate ES is driven by
ecological features and management practices within
specific landscapes (Reyers et al. 2013; Queiroz et al.
Fig. 6 ES bundles characterization based on the supply level and public awareness for final and intermediate ES
123
Landscape Ecol
2015), while the supply of final ES is mainly
associated with intensive management practices as a
result of high social demand and population growth in
coastal areas (Castro et al. 2014). For instance, the
social demand for tourism is linked with urban and
highly populated areas, as has been shown in previous
studies in Spain (Martın-Lopez et al. 2012) and
Denmark (Turner et al. 2014). This may be explained
by the type of tourism studied which is related to sun
and beaches. This is the opposite of the more rural
ecotourism located on internal areas in our case study
(Garcıa-Llorente et al. 2012, 2016; Quintas-Soriano
et al. 2016).
Similarly, food production from greenhouse horti-
culture shows a high spatial clustering defined as
agribusiness and associated with increasingly static
productivity, increasing capacity for innovation and
the stimulation of new business formations (Porter
2000; Schouten 2011). This landscape exhibits the
largest concentration of greenhouses in the world, that
produce and export vegetables to respond to the high
levels of national and international demand (Aznar-
Sanchez et al. 2011; Egea et al. 2017), representing
19% of the local economy (Sanchez-Picon 2005). The
high spatial clustering can be explained by the
suitable topographical conditions of the area, and
mirrors previous studies that show the predominance
of agriculture in certain areas with flat topography
(Raudsepp-Hearne et al. 2010; Turner et al. 2014).
Furthermore, the greenhouse production also benefits
from the groundwater supplies of an aquifer system
located in nearest mountains (Vallejos-Izquierdo et al.
2008; Quintas-Soriano et al. 2014; Castro et al. 2015).
Our results show that greenhouse horticulture produc-
tion does not co-occur with other ES supply, high-
lighting the negative impact or trade-offs on other ES
such as water regulation or habitat quality (e.g., see
Castro et al. 2015; Quintas-Soriano et al. 2016)
(Fig. 2).
Food production from traditional agriculture was
distributed more widely across less populated rural
areas, and associated to intermediate ES. This type of
agriculture is related to subsistence farming practices
at small scales. Cultural services such as the main-
taining of local breeds and varieties, local identity,
local ecological knowledge, and regulating services
such as water regulation and erosion control are often
linked to traditional agriculture (Sayadi et al. 2009;
Garcıa-Llorente et al. 2012).
We found the lowest ES diversity in the north of the
study area, coinciding with the lowest supply of
traditional agriculture, mainly in areas affected by
rural abandonment. Previous studies showed that the
study area traditionally had a high agrarian tradition
and currently is in an abandonment process (Fischer
et al. 2012; Iniesta-Arandia et al. 2015). Moreover,
this region has promoted subsistence agriculture
practices with very limited production for self-suffi-
ciency of the local residents of the mountains and rural
areas. However, in accordance with other studies
(Sayadi et al. 2009; Quintas-Soriano et al. 2016), our
results highlight food from traditional agriculture as
the second most important ES. Garcıa-Llorente et al.
(2012) also showed the importance of traditional
agriculture due to its role in the supply of cultural
services such as aesthetic values, local identity and
local ecological knowledge, and regulating services,
such as erosion control, hydrological regulation and
water quality.
Bridging the gap between ecological and social
perspectives in ES management
Efficient and sustainable ES management requires a
detailed knowledge about drivers and underlying
mechanisms of ES trade-offs and synergies (Bennett
et al. 2009), as well as the incorporation of social
values of local public. To date, there have been few
attempts to merge ecological (i.e., supply) and socio-
cultural (i.e., demand) dimensions in an ES bundle
analysis (i.e., see Baro et al. 2017 and Dittrich et al.
2017). This study presents a novel approach by
incorporating both ecological and social factors that
shape the supply and demand of ES bundles. However,
this integrating represents both a methodological
challenging, but also a limitation in order to evaluate
the validity if the assessment. One of the limitations
found here is in combining biophysical and social
factors to define ES bundles. The spatial scale used in
the analysis of ES bundles (i.e., municipality level)
(Raudsepp-Hearne et al. 2010; Renard et al. 2015;
Queiroz et al. 2015) requires normalizing and stan-
dardizing ES supply, resulting in loss of spatial
accuracy. We advanced on this limitation by using
GIS models (e.g., InVEST) instead of using proxies of
ES supply (Raudsepp-Hearne et al. 2010; Queiroz
et al. 2015), however, the averaging and standardiza-
tion process of ES supply at the municipality level
123
Landscape Ecol
remains a methodological challenge that requires a
solution and new protocols (Carpenter et al. 2009;
Martın-Lopez et al. 2012; Castro et al. 2014). Also, the
difficulty to incorporate two different-nature data (i.e.,
ecological and social) promote a gap regarding the
scale level used: social perceptions are linked to
individuals of the local public, and this information is
difficult to translate to a specific spatial scale. More-
over, social perceptions can be identified at the same
time for a specific landscape unit, land use or a whole
region. Because of all that, to homogenize and
translate all this complexity to a similar spatial unit
that ecological data, makes the methodology as one of
the major challenges in the transdisciplinary research
(Castro et al. 2014; Quintas-Soriano et al.
2014, 2018a, b).
The four types of ES bundles identified exemplified
the complexity of social and ecological factors that
operate in transformed landscapes. Only two bundles
(i.e., bundle 2 for final ES, and bundle 1 for
intermediate ES) were characterized as ‘‘coupled
bundles’’ where the supply level and public awareness
were both high. In addition, three types of mismatched
bundles were found corresponding with areas where
the ES supply and public awareness showed different
levels of de-coupling. For instance, medium and high
values of ES supply with low public awareness,
mismatch type A, (Fig. 6) demonstrates a need for
increased of social awareness of those ES. We found
that most bundles were identified within this category.
For instance, intermediate services such as water
regulation, climate regulation and soil protection were
found with the lowest perceived importance. These
results highlight the difficulty of the local public to
recognize the value of regulating services. This is
especially true in arid and semi-arid landscapes where
extremely arid lands are linked to unproductive
ecosystems and thus, are undervalued by the general
public (Castro et al. 2011; Lopez-Rodrıguez et al.
2015; Rodrıguez-Caballero et al. 2018). Those results
highlight that more effort is needed by policymakers
and researchers to raise awareness about the key role
of arid landscapes in the provision of intermediate
services. Our results also show how different areas
(defined by ES bundles) showed different levels of
social importance of ES, which emphasizes that
stakeholders’ perspectives are influenced by social,
economic, institutional, and ecological factors
(Turkelboom et al. 2018). Therefore, we argue that
better understanding of stakeholders’ preferences for
ES should be at the core of ES bundle analysis.
Actions in management and decision-making must
recognize the importance of incorporating the public
awareness for conservation strategies. The type B of
bundle mismatch is characterized by medium–high
levels of social awareness and low ES supply. As
previously shown by Anderson et al. (2015), this
bundle type highlights that the value (demand) placed
on a service is not necessarily connected to the
quantity (supply) of the service. In our case study, this
bundle type was localized in internal rural areas
affected by rural abandonment and the loss of
traditional agriculture practices. This result is consis-
tent with the trend of urban expansion observed in
Spain over the last four decades (Garcıa-Llorente et al.
2016). Consequently, we call to implement actions
that promote public participation in environmental
planning and decision-making (Miller 2005) and to
reconnect urban dwellers with rural areas (Garcıa-
Llorente et al. 2016). Further, there is a need to
combine formal knowledge with historically and
culturally consolidated experiential knowledge, tradi-
tions and practices to address the complexity of
ecosystem and biodiversity conservation objectives
(Martın-Lopez and Montes 2015). Finally, the type C
of bundle mismatch describes areas with low ES
supply and low social awareness. Bundles 3 for final
ES and 6 for intermediate ES were in this category. For
instance, the greenhouse production bundle represents
an area with low values of intermediate services where
there is also a lack of public awareness, which
emphasizes the need for raising social awareness
regarding the invisible processes that maintain multi-
functional landscapes. As pointed out by Castro et al.
(2014), our results are consistent with the need of
preserving intermediate ES (e.g., aquifer recharge) to
maintain the provision of final ES (e.g., food produc-
tion). Our study identified ES bundles with different
levels of decoupling, highlighting the need of new
land management strategies that address those mis-
matches in order to achieve a more sustainable use of
ES. It is clear that new strategies to increase social
awareness and reverse the bundles mismatches found
are needed. For instance, some key recommendations
are the promotion a culture of shared responsibility
among multiple stakeholders to launch real action at
the administration level for specific environmental
problems, and train and work more closely with
123
Landscape Ecol
managers and decision-makers to integrate the ES
framework and specifically the ES bundle approach
into the day-to-day management of natural spaces
(Quintas-Soriano et al. 2018a). Understanding and
characterizing ES bundles is a key challenge for
implementing ES approaches in land management and
planning. Our study demonstrates the importance of
integrating biophysical and socio-cultural dimensions
when mapping ES bundles. Our findings can be used
by land managers to identify areas in which ES are less
supply and low perceive as well as priority areas for
maximizing ES provision, and can help to identify
conflicts associated with new management and plan-
ning practices (Castro et al. 2018a). Incorporating both
ecological and social dimensions in the assessment of
ES brings ES trade-offs and bundle analysis closer to
the real-world realities spatial planners and decision-
makers are working with.
Acknowledgements Funding for the development of this
research was provided by the Andalusian Center for the
Assessment of Global Change (CAESCG) (GLOCHARID
project). C.Q.S. was funded by a grant from the University of
Almeria to perform a short research stay at the Stockholm
Resilience Centre to develop the present study. A.J.C. was
partially funded by the NSF Idaho EPSCoR Program and by the
National Science Foundation under award number IIA-
1301792. A grant from the Spanish National Institute for
Agriculture and Food Research and Technology (INIA), which
is co-funded by the Social European Fund provided support for
M.G.L. Special thanks for JuanMiguel Requena for his valuable
help and advices about R. This research is a contribution to the
Programme on Ecosystem Change and Society (www.pecs-
science.org).
References
Anderson E, Nykvist B, Malinga R, Jaramillo F, Lindborg R
(2015) A social-ecological analysis of ecosystem services
in two different farming systems. Ambio 44:102–112
Armas C, Miranda JD, Padilla FM, Pugnaire FI (2011) Special
issue: the Iberian Southeast. J Arid Environ 75:1241–1243
Aznar-Sanchez JA, Galdeano-Gomez E, Perez-Mesa JC (2011)
Intensive horticulture in Almerıa (Spain): a counterpoint to
current European rural policy strategies. J Agrar Change
11:241–261
Balvanera P, Calderon-Contreras R, Castro AJ, Felipe-Lucia
MR, Geijzendorffer IR, Jacobs S, Martın-Lopez B, Arbieu
U, Speranza CI, Locatelli B, Harguindeguy NP, Mercado
IR, Spierenburg MJ, Vallet A, Lynes L, Gillson L (2017)
Interconnected place-based social–ecological research can
inform global sustainability. Curr Opin Environ Sustain
29:1–7
Baro F, Gomez-Baggethun E, Haase D (2017) Ecosystem ser-
vice bundles along the urban-rural gradient: insights for
landscape planning and management. Ecosys Serv
24:147–159
Bastian O, Haase D, Grunewald K (2012) Ecosystem properties,
potentials and services—the EPPS conceptual framework
and an urban application example. Ecol Indic 21:7–16
Bateman IJ, Harwood AR, Mace GM, Watson RT, Abson DJ,
Andrews B, Binner A, Crowe A, Day BH, Dugdale S, Fezzi
C, Foden J, Hadley D, Haines-Young R, Hulme M, Kon-
toleon M, Lovett AA, Munday P, Pascual U, Paterson J,
Perino G, Sen A, Siriwardena G, van Soest D, Termansen
M (2013) Bringing ecosystem services into economic
decision-making: land use in the United Kingdom. Science
341:45–50
Bennett EM, Cramer W, Begossi A, Cundill G, Dıaz S, Egoh
BN, Geijzendorffer IR, Krug CB, Lavorel S, Lazos E,
Lebel L, Martın-Lopez B, Meyfroidt P, Mooney HA, Nel
JL, Pascual U, Payet K, Perez Harguindeguy N, Peterson
GD, Prieur-Richard AH, Reyers B, Roebeling P, Seppelt R,
SolanM, Tschakert P, Tscharntke T, Turner BL II, Verburg
PH, Viglizzo EF,White PCL,Woodward G (2015) Linking
biodiversity, ecosystem services, and human well-being:
three challenges for designing research for sustainability.
Curr Opin Environ Sustain 14:76–85
Bennett EM, Peterson GD, Gordon LJ (2009) Understanding
relationships amongmultiple ecosystem services. Ecol Lett
12:1394–1404
Carpenter SR, Folke C, Scheffer M, Westley FR (2009) Resi-
lience: accounting for the noncomputable. Ecol Soc
14(1):13
Castro AJ, Julian JP, Vaughn C, Martin-Mikle CJ, Quintas-
Soriano C (2018a) Ecosystem services across US-water-
sheds: a meta-analysis 2001–2014. Ecosystem services and
global ecology. Levente Hufnagel, Intechopen, pp 81–101
Castro AJ, Martın-Lopez B, Garcıa-Llorente M, Aguilera PA,
Lopez E, Cabello J (2011) Social preferences regarding the
delivery of ecosystem services in a semiaridMediterranean
region. J Arid Environ 75(11):1201–1208
Castro AJ, Martın-Lopez B, Lopez E, Plieninger T, Alcaraz-
Segura D, Vaughn CC, Cabello J (2015) Do protected areas
networks ensure the supply of ecosystem services? Spatial
patterns of two nature reserve systems in semi-arid Spain.
Appl Geogr 60:1–9
Castro AJ, Quintas-Soriano C, Brandt J, Atkinson CL, Baxter
CV, Burnham M, Egoh B, Garcıa-Llorente M, Julian JP,
Martın-Lopez B, Liao F, Running K, Vaughn C, Norstrom
A (2018b) Applying place-based social-ecological
research to address water scarcity: insights for future
research. Sustainability 10:1516
Castro AJ, Vaughn C, Garcıa-Llorente M, Julian JP, Atkinson
CL (2016a) Willingness to pay for ecosystem services
among stakeholder groups in a South-Central U.S. water-
shed with regional conflict. J Water Resour Plan Manag
142:05016006
Castro AJ, Vaughn C, Julian JP, Garcıa-Llorente M (2016b)
Social demand for ecosystem services and implications for
watershed management. JAWRA J Am Water Resour
Assoc 52:209–221
Castro AJ, Verburg P, Martın-Lopez B, Garcıa-Llorente M,
Cabello J, Vaughn C, Lopez E (2014) Ecosystem service
123
Landscape Ecol
trade-offs from the supply to social demand: a landscape-
scale spatial analysis. Landsc Urban Plan 132:102–110
Crouzat E, Mouchet M, Turkelboom F, Byczek C, Meersmans J,
Berger F, Verkerk PJ, Lavorel S (2015) Assessing bundles
of ecosystem services from regional to landscape scale:
insights from the French Alps. J Appl Ecol 52:1145–1155
D’Odorico P, Carr JA, Laio F, Ridolfi L, Vandoni S (2014)
Feeding humanity through global food trade. Earth’s
Future 2(9):458–469
Derkzen ML, van Teeffelen AJA, Verburg H (2015) Quantify-
ing urban ecosystem services based on higher solution data
of urban Green space: an assessment for Rotterdam, the
Netherlands. J Appl Ecol 52:1020–1032
Dittrich A, Seppelt R, Vaclavık T, Cord AF (2017) Integrating
ecosystem service bundles and socio-environmental con-
ditions—a national scale analysis from Germany. Ecosys
Serv 28:273–282
Egea FJ, Torrente RG, Aguilar A (2017) An efficient agro-in-
dustrial complex in Almerıa (Spain): towards an integrated
and sustainable bioeconomy model. New Biotechnol
40:103–112
Eigenbrod F, Bell VA, Davies HN, Heinemeyer A, Armsworth
PR, Gaston KJ (2011) The impact of projected increases in
urbanization on ecosystem services. Proc R Soc B
278(1722):3201–3208
Ellis EC (2011) Anthropogenic transformation of the terrestrial
biosphere. Philos Trans R Soc A 369:1010–1035
Fischer J, Hartel T, Kuemmerle T (2012) Conservation policy in
traditional farming landscapes. Conserv Lett 5:167–175
Fisher B, Turner RK, Morling P (2009) Defining and classifying
ecosystem services for decision making. Ecol Econ
68:643–653
Foley JA, DeFries R, Asner GP, Barford C, Bonan G, Carpenter
SR, Chapin SC, Coe MT, Daily GC, Gibbs HK, Helkowski
JH, Holloway T, Howard EA, Kucharik CJ, Monfreda C,
Patz JA, Prentice IC, Ramankutty N, Snyder PK (2005)
Global consequences of land use. Science 309:570–574
Garcıa-Llorente M, Castro AJ, Quintas-Soriano C, Lopez I,
Castro H, Montes C, Martın-Lopez B (2016) The value of
time in biological conservation and supplied ecosystem
services: a willingness to give up time exercise. J Arid
Environ 124:13–21
Garcıa-Llorente M, Martın-Lopez B, Nunes PALD, Castro AJ,
Montes C (2012) A choice experiment study for land use
scenarios in semi-arid watersheds environments. J Arid
Environ 87:219–230
Goldstein JH, Caldarone G, Duarte TK, Ennaanay D, Hannahs
N, Mendoza G, Polasky S, Wolny S, Daily GC (2012)
Integrating ecosystem-service tradeoffs into land-use
decisions. PNAS 109:7565–7570
Hamann M, Biggs R, Reyers B (2015) Mapping social–eco-
logical systems: identifying ‘green-loop’ and ‘redloop’
dynamics based on characteristic bundles of ecosystem
service use. Glob Environ Change 34:218–226
Hicks CC, Cinner JE (2014) Social, institutional, and knowledge
mechanisms mediate diverse ecosystem service benefits
from coral reefs. PNAS 111(50):17791–17796
Iniesta-Arandia I, Garcıa del Amo D, Garcıa-Nieto AP, Pineiro
C, Montes C, Martın-Lopez B (2015) Factors influencing
local ecological knowledge maintenance in Mediterranean
watersheds: insights for environmental policies. Ambio
44:285–296
Iniesta-Arandia I, Garcıa-Llorente M, Aguilera P, Montes C,
Martın-Lopez B (2014) Socio-cultural valuation of
ecosystem services: uncovering the links between values,
drivers of change, and human well-being. Ecol Econ
108:36–48
Lopez-Rodrıguez MD, Castro AJ, Castro H, Jorreto S, Cabello J
(2015) Science–policy interface for addressing environ-
mental problems in arid Spain. Environ Sci Policy 50:1–14
MacDonald GK, Brauman KA, Sun S, Carlson KM, Cassidy ES,
Gerber JS, West PC (2015) Rethinking agricultural trade
relationships in an era of globalization. Bioscience
65:275–289
Maes J, Egoh B, Willemen L, Liquete C, Vihervaara P,
Schagner JP, Grizzetti B, Drakou EG, La Notte A, Zulian
G, Bouraoui F, Paracchini ML, Braat L, Bidoglio G (2012)
Mapping ecosystem services for policy support and deci-
sion making in the European Union. Ecosys Serv 1:31–39
Martın-Lopez B, Iniesta-Arandia I, Garcıa-Llorente M, Palomo
I, Casado-Arzuaga I, Garcıa del Amo D, Gomez-Bag-
gethun E, Oteros-Rozas E, Palacios-Agundez I, Willaarts
B, Gonzalez JA, Santos-Martın F, Onaindia M, Lopez-
Santiago C, Montes C (2012) Uncovering ecosystem ser-
vice bundles through social preferences. PLoS ONE
7:e38970
Martın-Lopez B, Montes C (2015) Restoring the human
capacity for conserving biodiversity: a social-ecological
approach. Sustain Sci 10(4):699–706
Miller JR (2005) Biodiversity conservation and the extinction of
experience. Trends Ecol Evol 20:430–434
Munoz-Rojas M, De la Rosa D, Zavala LM, Jordan A, Anaya-
Romero M (2011) Changes in land cover and vegetation
carbon stocks in Andalusia, Southern Spain (1956–2007).
Sci Total Environ 409:2796–2806
Nieto-Romero M, Oteros-Rozas E, Gonzalez JA, Martın-Lopez
B (2014) Exploring the knowledge landscape of ecosystem
services assessments in Mediterranean agroecosystems:
insights for future research. Environ Sci Policy 37:121–133
Oksanen J, Blanchet GF, Friendly M, Kindt R, Legendre P,
McGlinn D, Minchin PR, O’Hara RB, Simpson GL,
Solymos P, Stevens MHH, Szoecs E, Wagner H (2018)
Vegan: community ecology package. R package version
2.5-2. https://CRAN.R-project.org/package=vegan
Opdam P (2013) Using ecosystem services in community-based
landscape planning: science is not ready to deliver. In: Fu
B, Jones K (eds) Landscape ecology for sustainable envi-
ronment and culture. Springer, the Netherlands, pp 77–101
Plieninger T, Dijks S, Oteros-Rozas E, Bieling C (2013)
Assessing, mapping, and quantifying cultural ecosystem
services at community level. Land Use Policy 33:118–129
Porter ME (2000) Locations, clusters, and company strategy. In:
Clark GL, Feldman P, Gertler MS (eds) The Oxford
handbook of economic geography. Oxford University
Press, Oxford, p 274
Queiroz C, MeachamM, Richter K, Norstrom AV, Anderson A,
Norberg J, Peterson G (2015) Mapping bundles of
ecosystem services reveals distinct types of multifunc-
tionality within a Swedish landscape. Ambio 44:89–101
Quintas-Soriano C, Brandt J, Running K, Baxter CV, Gibson
DM, Narducci J, Castro AJ (2018a) Social-ecological
123
Landscape Ecol
systems influence ecosystem service perception: a pro-
gramme on ecosystem change and society (PECS) analysis.
Ecol Soc 23(3):3
Quintas-Soriano C, Castro AJ, Castro H, Garcıa-Llorente M
(2016) Impacts of land use change on ecosystem services
and implications for human well-being in Spanish dry-
lands. Land Use Policy 54:534–548
Quintas-Soriano C, Castro AJ, Garcıa-Llorente M, Cabello J,
Castro H (2014) From supply to social demand: a land-
scape-scale analysis of the water regulation service.
Landscape Ecol 29:1069–1082
Quintas-Soriano C, Garcıa-Llorente M, Castro AJ (2018b)What
has ecosystem service science achieved in Spanish dry-
lands? Evidences of need for transdisciplinary science.
J Arid Environ 159:4–10
R Core Team (2018) R: a language and environment for sta-
tistical computing. R Foundation for Statistical Comput-
ing, Vienna, Austria. Available online at https://www.R-
project.org/
Raudsepp-Hearne C, Peterson GD, Bennett EM (2010)
Ecosystem service bundles for analyzing tradeoffs in
diverse landscapes. PNAS 107:5242–5247
Renard D, Rhemtulla JM, Bennett EM (2015) Historical
dynamics in ecosystem service bundles. PNAS
112:13411–13416
Requena-Mullor JM, Quintas-Soriano C, Brandt J, Cabello J,
Castro AJ (2018) Modeling how land use legacy affects the
provision of ecosystem services in Mediterranean southern
Spain. Environ Res Lett 13:114008
Reyers B, Biggs R, Cumming GS, Elmqvist T, Hejnowicz AP,
Polasky S (2013) Getting the measure of ecosystem ser-
vices: a social–ecological approach. Front Ecol Environ
11(5):268–273
Rodrıguez-Caballero E, Castro AJ, Chamizo S, Quintas-Soriano
C, Garcıa-Llorente M, Canton Y, Weber W (2018)
Ecosystem services provided by biocrusts: from ecosystem
functions to social values. J Arid Environ 159:45–53
Sanchez-Picon A (2005) De frontera a milagro. La confor-
macion historica de la economıa almeriense. En editores
Caja Rural Intermediterranea. Cajamar. La economıa de la
Provincia de Almerıa. ISBN: 84-95531-27-5, pp 704
Sayadi E, Gonzalez-Roa M, Calatrava Requena J (2009) Public
preferences for landscape features: the case of agricultural
landscape in mountainous Mediterranean areas. Land Use
Policy 26:334–344
Schouten MA (2011) How can clusters in agriculture be mea-
sured and identified in the Netherlands? Clusters agricul-
ture. Economics and Policy (BEB) Agricultural Economics
and Rural Policy Group, Wageningen
Turkelboom F, Leone M, Jacobs S, Kelemen E, Garcıa-Llorente
M, Baro F, Termansen M, Barton DN, Berry P, Stange E,
Thoonen M, Kaloczkai A, Vadineanu A, Castro AJ, Czucz
B, Rockmann C, Wurbs D, Odee D, Preda E, Gomez-
Baggethun E, Rusch GM, Martınez-Pastur G, Palomo I,
Dick J, Casaer J, van Dijk J, Priess JA, Langemeyer J,
Mustajoki J, Kopperoinen L, Baptist MJ, Peri PL,
Mukhopadhyay R, Aszalos R, Roy SB, Luque S, Rusch V
(2018) When we cannot have it all: ecosystem services
trade-offs in the context of spatial planning. Ecosys Serv
29:566–578
Turner KG, OdgaardMC, Bøcher PK, Dalgaard T, Svenning J-C
(2014) Bundling ecosystem services in Denmark: trade-
offs and synergies in a cultural landscape. Landsc Urban
Plan 125:89–104
Vallejos-Izquierdo A, Pulido Bosch A, Daniele D, Martın
Rosales W (2008) The intensive exploitation of aquifers
and its implications for sustainable water management in a
semi-arid zone (Almerıa, SE Spain). Paper presented at the
Iahr international groundwater symposium: flow and
transport in heterogeneous subsurface formations: theory
modelling and applications (Estambul (Turquıa)), Bogazici
Universitesi (Instambul), Estambul (Turquıa), pp 657–664
Vigl LE, Tasser E, Schirpke U, Tappeiner U (2017) Using land
use/land cover trajectories to uncover ecosystem service
patterns across the Alps. Reg Environ Change
8:2237–2250
Yang G, Ge Y, Xue H, Yang W, Shi Y, Peng C, Du Y, Fan X,
Ren Y, Chang J (2015) Using ecosystem service bundles to
detect trade-offs and synergies across urban–rural com-
plexes. Landsc Urban Plan 136:110–121
Publisher’s Note Springer Nature remains neutral with
regard to jurisdictional claims in published maps and
institutional affiliations.
123
Landscape Ecol