This study was conducted in a rural-urban gradient in southern Spain that comprises the Alto Genil watershed, including part of the Sierra Nevada mountain range, part of the Granada valley and the city of Granada (Fig. 1). The study area comprises 32 municipalities and nearly 113,130 hectares. Altitude along the gradient varies from 500 metres a.s.l. in the Granada valley to 3,400 metres a.s.l. in the highest peaks of the Sierra Nevada mountain range.

Figure 1.  

Map of the study area.

Within the mountain range, two natural protected areas are present: the Sierra Nevada Natural Park, which was designated in 1989 and the Sierra Nevada National Park, which was designated in 1999, with 13,057 and 17,817 hectares respectively. While in the Sierra Nevada National Park, anthropic activities are highly restricted, the Sierra Nevada Natural Park conservation policies are less strict, allowing traditional practices such as livestock raising and important economic activities such as the Sierra Nevada ski resort (García-Nieto et al. 2013). The Sierra Nevada protected areas have the greatest diversity of plant species in the Iberian Peninsula (over 2,200 taxon) (Junta de Andalucía 2011), although they have suffered important land use changes from cereal crops, pastures and Mediterranean shrublands to coniferous plantations during the 1950s (Abellán 1981,Padilla et al. 2010). The Sierra Nevada protected areas are also characterised by the confluence of multiple land uses, such as tourism and agriculture (Junta de Andalucía 2011) and their function as a natural water reservoir for human consumption and agriculture in the lowlands (Moreno et al. 2014).

The Granada valley has historically been one of the most productive areas of Spain and directly depends on the Sierra Nevada mountain range water reservoir. There are three remarkable periods in the history of the Granada valley based on the dominant crops: flax and hemp (18th-19th centuries), beetroot (20th century) and tobacco (20th century) (Menor Toribio 2000). This situation changed during the 1950s and specially from the 1970s until today, when massive migrations from rural to urban areas occurred due to the loss of agriculture economic potential (Villegas Molina and Sánchez del Árbol 1997). These migrations favoured an urban expansion along peri-urban areas, leading to the destruction of rural community structure, the degradation of agrarian landscapes, the loss of local identity and the occupation of fertile areas by built infrastructure (Menor Toribio 1997).

The city of Granada is the fourth largest town in Andalusia and the sixteenth in Spain with over 230,000 inhabitants. Granada comprises 8,802 hectares, which is only 0.7% of the total surface area of the Province of Granada, but harbours 25.6% of the total population. This, combined with the fact that 30.3% of the population lives in peri-urban municipalities (which comprise 6.1% of the province’s surface area), means that more than one half of the population of the province lives in urban and peri-urban areas. The city of Granada has become a focus of interest for the tourism industry, particularly for its Andalusí history and architecture and the castle of the Alhambra, which drew over 2.5 million tourists in 2016.

A participatory mapping process was developed to assess the supply and demand of ES within the study area and to identify key elements to be considered in a new integrated landscape planning scheme. First, we identified and interviewed local stakeholders to characterise the most important and vulnerable ES in the area; then, we developed a one-day participatory mapping workshop to identify the main supply and demand areas of ES; and finally, we analysed the results in terms of ES flows (Fig. 2). Here we refer to ES flows as the joint analysis of ES supply and demand, but we have not analysed the spatial connectivity nor the processes that affect ES flows (Bagstad et al. 2013).

Figure 2.  

Scheme of the methodological design.

The matrix created from the interviewees' answers allowed us to select three ES from each category based on their importance and vulnerability: water for humans and irrigation, agricultural products and livestock products (provisioning services); habitat for species, air quality and soil fertility (regulating services); and aesthetic value, traditional ecological knowledge and rural and nature tourism (cultural services) (Fig. 4).

Figure 4.  

Scatter plot of the importance (X axis) and vulnerability (Y axis) of ES as perceived by key stakeholders during the interviews. Blue, green and orange dots represent provisioning, regulating and cultural services respectively. The names in bold are the selected ES for the workshop.

Overall, the maps did not reveal a clear pattern of supply areas for each typology of ES. The dots were quite uniformly distributed along the territory, but we found that the density was slightly higher in the Sierra Nevada mountain range and the Granada valley poplar groves. Regarding the results for each ES, (1) the Sierra Nevada mountain range was mainly characterised as a supplier of water, livestock products, habitat for species, tourism and aesthetic values and (2) the Granada valley was mainly characterised as a supplier of agricultural products, soil fertility and traditional ecological knowledge (Fig. 5).

Figure 5.  

ES supply areas resulting from the workshop. W: water for humans and irrigation; AP: agricultural products; LP: livestock products; P_ES: provisioning services; HS: habitat for species; AQ: air quality; SF: soil fertility; R_ES: regulating services; T: tourism; AV: aesthetic value; TEK: traditional ecological knowledge; C_ES: cultural services.

Maps of ES demand showed more clear spatial patterns. The areas with the highest demand for every ES were Granada city and other peri-urban areas, although demand was lower for soil fertility and traditional ecological knowledge. On the other hand, the services in greatest demand in the Sierra Nevada mountain range were habitat for species and air quality and the services in greatest demand in Granada valley were water for humans and irrigation, air quality and soil fertility (Fig. 6).

Figure 6.  

ES demand areas resulting from the workshop: W: water for humans and irrigation; AP: agricultural products; LP: livestock products; P_ES: provisioning services; HS: habitat for species; AQ: air quality; SF: soil fertility; R_ES: regulating services; T: tourism; AV: aesthetic value; TEK: traditional ecological knowledge; C_ES: cultural service.

The participants also identified several other Spanish provinces and European countries where some of the ES supplied in the study area were demanded. Habitat for species, rural and nature tourism, aesthetic value and traditional ecological knowledge were identified as the most demanded ES in other European countries, while rural and nature tourism, aesthetic value and livestock products were identified as the most demanded ES in other areas of Spain.

There were statistically significant differences in the supply of ES amongst the different land protection categories (Kruskal-Wallis; \(\chi^2\)=100.76; p-value<0.001). ES supply of Sierra Nevada National Park was significantly higher than the supply of non-protected areas and urban areas; Sierra Nevada Natural Park also showed higher supply than urban areas (Dunn’s test, p<0.05). On the other hand, there were no statistically significant differences betweenSierra Nevada Natural Park and non-protected areas and between Sierra Nevada National Park and Sierra Nevada Natural Park. The highest mean supply values corresponded to Sierra Nevada National Park (\(\bar{x}\)=4.80) and Natural Park (\(\bar{x}\)=4.43), followed by non-protected areas (\(\bar{x}\)=4.10) and urban areas (\(\bar{x}\)=2.45) (Fig. 7).

Figure 7.  

Boxplots of the intensity of ES supply (left) and demand (right) in the different land protection categories of the study area. Capital letters below the name indicate if there is any statistically significant difference between the areas (different letter) or not (same letter) with a significance level of 0.05.

There were also statistically significant differences amongst land protection categories in ES demand (Kruskal-Wallis; \(\chi^2\)=373.66; p-value<0.001). Contrary to the supply results, urban areas had a significantly higher demand, while Sierra Nevada National Park had a significantly lower demand (Dunn’s test, p<0.05). The highest mean demand value corresponded to urban areas (\(\bar{x}\)=13.900), followed by non-protected areas (\(\bar{x}\)=2.30), Sierra Nevada Natural Park (\(\bar{x}\)=1.53) and Sierra Nevada National Park (\(\bar{x}\)=0.76) (Fig. 7).

There was a significant positive correlation (r_s=0.74; p-value<0.001) between ES supply and altitude; the higher the altitude along the gradient, the greater the intensity in the supply of ES. Nonetheless, between 500 and 800 metres altitude, the supply intensity progressively decreases and reaches a minimum at 700 metres. The intensity values between 800 and 2,500 metres altitude remain relatively stable with similar values to those found at 500-600 metres. Between 2,500 and 3,300 metres altitude, the intensity tends to increase again with small oscillations, reaching a maximum at 3,300 metres (Fig. 8).

Figure 8.  

Scatter plots showing the relationship between altitude and the supply and demand of ES in the study area.

Unlike the results for ES supply, there was a negative correlation (r_s=-0.84; p-value<0.001) between ES demand and altitude. In this case, the higher the altitude along the gradient the lower the intensity in ES demand. We found the highest values of demand between 500 and 900 metres altitude, where Granada valley and most of the urban cores are located. Demand values start to decrease from there to the higher areas, until 2,200-2,400 metres altitude, where the Pradollano ski resort is located, creating another important ES demand peak (Fig. 8).

Four groups of municipalities were clearly distinguished in the study area (HCA dissimilarity coefficient = 60.6) (Suppl. materials 2, 3). The first group (G1) was formed by municipalities in the Granada valley and it is characterised by having the highest percentage of agricultural areas and population mostly employed in the primary and secondary sectors. The second group (G2) was formed by peri-urban municipalities, which have a high percentage of altered and constructed areas, population employed in the tertiary sector and a high population density. The third group (G3) was mostly composed of municipalities of the Sierra Nevada mountain range, with a high percentage of forest areas and Natural Protected Areas and with a high number of touristic rural establishments. Finally, the fourth group (G4) was only represented by the municipality of Granada, mainly characterised by having a high percentage of employed population in the tertiary sector, the highest population density and a high number of hotels and hostels (Fig. 9).

Figure 9.  

Hierarchical cluster analysis results, showing the four groups of municipalities (see Suppl. materials 2-3 for a more detailed information).

We found statistically significant differences in the supply of ES amongst the four groups of municipalities (Kruskal-Wallis; \(\chi^2\)=134.44; p-value<0.001). Group 1 was significantly different from groups 2, 3 and 4; while group 2 was significantly different from groups 1, 3 and 4; and groups 3 and 4 were significantly different from groups 1 and 2 (Dunn’s test, p-value<0.001). Groups 3 and 4 did not show significant differences between them (Dunn’s test, p-value=0.46) (Fig. 10). The highest mean supply value corresponded to municipalities clustered in group 1 (\(\bar{x}\)=4.71), followed by groups 3 (\(\bar{x}\)=3.60), 4 (\(\bar{x}\)=3.50) and 2 (\(\bar{x}\)=1.87).

Figure 10.  

Boxplots of the intensity of ES supply (left) and demand (right) in the four groups of municipalities in the study area. Capital letters below the name indicate if there is any statistically significant difference between the areas (different letter) or not (same letter) with a significance level of 0.05.

We also found statistically significant differences amongst the four groups of municipalities in their demand of ES (Kruskal-Wallis; \(\chi^2\)=281.21; p-value<0.001). Here, every group was significantly different from every other group and the groups with the highest mean demand values were those related to the urban cores, namely, groups 2 (\(\bar{x}\)=11.38) and 4 (\(\bar{x}\)=9.27) (Fig. 10).

The results of the questionnaires completed after the workshop revealed the perceptions of the stakeholders about the utility and applicability of participatory mapping of ES. As a result, 68.4% of the participants considered this methodology a very important tool to reveal the existing relationships between rural and urban areas. On the other hand, 26.3% of participants considered the process important to reveal and contrast the different perspectives and opinions of the population, as well as to clarify concepts and to provide information about territorial planning. Finally, only one participant thought that the method was not very useful and that, in order to be operative, it should be more closely linked to concrete actions in the territory (Fig. 11).

Figure 11.  

Summary of the most frequent perceptions of the stakeholders, revealed after the workshop, about the utility and applicability of participatory mapping of ES.

This study provides valuable information about ES flows along the rural-urban gradient of the Sierra Nevada mountain range, the Granada valley and the city of Granada. Our participatory mapping exercise revealed that the city of Granada and other peri-urban cores are high demand areas for ES with little supply, while Granada valley and, especially, the Sierra Nevada Natural and National Parks are high supply areas of critical ES. Our analyses also revealed the great importance of the valley as a supply area, especially of agricultural products, soil fertility and traditional ecological knowledge; however, this supply directly depends on the demand of a key ES supplied by the Sierra Nevada mountain range: water for human consumption and for agriculture. Our results are consistent with previous studies that highlight that the growing population and expansion of cities is leading to a growing demand for ES provided elsewhere (Burger et al. 2012, Liu et al. 2015, Pascual et al. 2017a). In an increasingly interconnected world, a specific management strategy applied at a local level could impact distant ecosystems and this should be taken into account when developing integrated landscape planning schemes (Liu et al. 2015, Pascual et al. 2017a).

On the local scale, our results are consistent with those of Palomo et al. (2013) who reported that protected areas at higher altitudes are critical suppliers of ES, which have a scale of beneficiaries that reaches from the local to the global. The differences in ES supply observed along the altitudinal gradient might be related to changes in the predominant land uses at different altitude intervals, although this hypothesis needs further research. Considering that the mountain areas are key elements to maintain the supply of ES in the valley, it is essential that landscape planning schemes preserve the ES supply capacity within the mountain range in order to maintain human well-being and to achieve ecosystem sustainability. Since the mountain range and the valley municipalities had the highest supply of ES rates, they would be key elements in regional policies. For example, as Rodríguez-Loinaz et al. (2015) suggest, these municipalities could be potential beneficiaries of government funds for their contribution to human well-being and landscape sustainability. Further, our results also highlight the need for increasing institutional efforts to enhance the supply of ES in the urban and peri-urban areas, taking into account their great demand and dependence from ES generated in other areas of the rural-urban gradient.

It seems urgent to include the existing relationships between ES supply and demand within decision-making processes if we take into account the most pressing drivers of change currently affecting our study area: abandonment of agriculture and expansion of urban areas in the Granada valley (Ruiz 2017) and climate change (Palomo 2017). These two main drivers of change have different origins and scales of impact: while the first responds to regional economic dynamics, the latter is a global process. This also occurs in some cases with the supply of ES, where the beneficiaries of the supplied services include the whole range from local to global beneficiaries (Burkhard et al. 2014). Our results show that several provisioning and cultural ES are highly demanded services in other provinces of Spain and countries of Europe, which highlights the ecological and cultural relevance of the study area.

Although many studies have analysed the supply of ES through mapping techniques, few have also integrated the demand to reveal ES flows (Beier et al. 2008, Brown et al. 2012, Nedkov and Burkhard 2012, Syrbe and Walz 2012, Wolff et al. 2015). The number of studies is even lower if we consider participatory techniques for mapping ES flows (Brown and Fagerholm 2015). On the other hand, few studies have been used to support decision-making or have been applied to landscape planning (Guerry et al. 2015, Ruckelshaus et al. 2015), but many studies acknowledge the potential applications of the mapped data to achieve these goals (Brown and Fagerholm 2015). Since political measures and landscape planning directly impact ecosystems and their capacity to supply ES (Crossman et al. 2013a), there is an urgent need to quantify and include the stocks and flows of ES in decision-making processes (Burkhard et al. 2013).

Mapping ES provides information and indicators about the current status and the trends of ES (Maes et al. 2012), allowing decision-makers to identify drivers of change affecting ecosystems and the services they provide (Palomo et al. 2014a, Maes et al. 2012, Hauck et al. 2013). Furthermore, including the flow of ES across the landscape would contribute to identifying mismatches between supply and demand, that is, situations where beneficiaries have an unsatisfied demand or where the uptake is higher than the stocks (Baró et al. 2016, Burkhard et al. 2012). Therefore, mapping the flow of ES provides relevant information to decision-makers that would contribute to the development of science-based policy-making as well as to enhance the sustainable use of ES (Hauck et al. 2013).

Within this framework, the preservation of the flow of ES must be a priority in landscape planning that could be approached through the integration of the participatory mapping of ES in decision-making processes, making it easier to prioritise the actions that are needed in plans or policies affecting the system (Baró et al. 2016). Thus, questions such as where to preserve biologically important areas (Cox et al. 2014), where to preserve areas that are potentially threatened or vulnerable to overuse (Hauck et al. 2013, van Riper et al. 2012), or where to restore ecosystems and how much to invest in green infrastructure (Maes et al. 2012) would have a much more informed answer if ES supply and demand areas have been previously identified. Our results suggest the need to change landscape planning schemes from their current approach based on administrative boundaries to a more comprehensive approach that considers the landscape as a whole: an integrated system based on social-ecological limits that includes the areas of supply and the beneficiaries of the ES (Fagerholm et al. 2013, Palomo et al. 2014b).

The participatory and deliberative process provided a significant amount of information that reveals some of the strengths and limitations of participatory mapping of ES, some of which have been previously mentioned in literature (Table 2). We identified and characterised some of the advantages and disadvantages of applying this methodology during a post-workshop meeting with the facilitators and analysing the recordings of the deliberations that took place in each group of participants. In our study case, participatory mapping of ES provided valuable information about the perceptions and knowledge of the participants regarding supply and demand of nine ES, which is a considerable number to operationalise the ES framework (IFAD 2009). The whole participatory process also helped us to identify key elements to lay the foundation for more integrated landscape planning, although combining this information with biological and ecological GIS data would increase the efficiency of management decisions (Cox et al. 2014). The study also revealed the existing flows of ES within the system, making the relationships among the three main geographic areas of the rural-urban gradient more visible for participants. Another strong point of the methodology is the fact that it allowed the mapping of some cultural ES (e.g. aesthetic value and traditional ecological knowledge) that otherwise would be difficult to evaluate using other mapping techniques (Hauck et al. 2013, Plieninger et al. 2013). Cultural services should be considered as key elements for the participatory mapping of ES since they provide information about the contribution of ES to non-material dimensions of human well-being and can thus contribute to preventing unwanted trade-offs in land management (Brown et al. 2012, Plieninger et al. 2013).

An important limitation that should be acknowledged relates to the necessarily high investment in time and human capital. Participatory workshops require the active involvement of many actors from different sectors and it is not always easy to motivate these actors to participate and to bring them together to discuss these issues. In our case, it took more than three months to establish contact and interview the key stakeholders.

Despite the limitations outlined above, we conclude that including participation in ES mapping greatly helps decision-makers to better value the contribution of ES to human well-being (Crossman et al. 2013a) and to better understand the management preferences of the stakeholders and what is or is not important to them. Thus, decision-makers would have a practical toolset to make informed decisions that would be more easily supported by the public and to reduce conflicts over changing policies (Cox et al. 2014, van Riper et al. 2012).

Additionally, we consider it necessary to incorporate the participation of citizens in strategic landscape planning. First, because participation fosters a citizenship that is active, organised and aware of the problems that affect their territory and stakeholders can feel that they are part of the planning process (Klain and Chan 2012, Manero 2010). Second, because citizens are experts in the territory with important traditional ecological knowledge, the deliberative processes become enriched and more complete than technicians and researchers could achieve by themselves (García-Nieto et al. 2013, Martín-López et al. 2012).