One Ecosystem :
Research Article
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Corresponding author: Natalia Alvarado-Arias (n.alvarado@alumnos.upm.es), Vinicio Moya-Almeida (vinicio.moya@udla.edu.ec)
Academic editor: Bastian Steinhoff-Knopp
Received: 28 Jan 2023 | Accepted: 01 Jun 2023 | Published: 10 Jul 2023
© 2023 Natalia Alvarado-Arias, Vinicio Moya-Almeida, Francisco Cabrera-Torres, Andrea Medina-Enríquez
This is an open access article distributed under the terms of the Creative Commons Attribution License (CC BY 4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Citation:
Alvarado-Arias N, Moya-Almeida V, Cabrera-Torres F, Medina-Enríquez A (2023) Evaluation and mapping of the positive and negative social values for the urban river ecosystem. One Ecosystem 8: e101122. https://doi.org/10.3897/oneeco.8.e101122
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Urban rivers play a crucial role in providing ecosystem services (ES) that contribute to the social well-being and quality of life of urban inhabitants. However, rapid urbanisation has led to the progressive degradation of these rivers, affecting their capacity to deliver ES and resulting in significant socio-ecological impacts. This study performs a participatory mapping of the non-monetary social values (positives and negatives), in the urban Zamora and Malacatos Rivers and their ESs, in Loja, Ecuador, to understand community perceptions and preferences in a context of degraded landscapes as a complementary category of analysis to traditional approaches. Methodologically, the collection, analysis and mapping were carried out using public participation GIS (PPGIS) based on surveys. This method facilitated the integration of social data with biophysical variables. The most relevant of the ten social values studied were positives: Learning, Aesthetic, Therapeutic and negatives: Displeasure, Deficient and Inaccessible Infrastructure and Threat of Flooding. We revealed different spatial patterns for each ES social value, where positive value locations exhibited a dispersed pattern, with clusters in peripheral areas, while negative value locations exhibited a clustered pattern in the city centre. The environmental variable with the most significant contribution was the Horizontal Distance to Green Areas. These findings enhance our understanding of the social values and preferences associated with ES in urban river contexts. Furthermore, they provide valuable insights for identifying areas of opportunity and conflict, informing community planning and effective management of the urban landscape.
ecosystem services, anthropogenic landscape, urban ecosystem services, public participation GIS, participatory mapping, stakeholders' perceptions
Rivers are not simply bodies of water; they are complex socio-ecological systems that provide a wide range of ecosystem services (ES) to people (
These anthropogenic pressures are particularly exacerbated in the context of developing cities in the Latin American and Caribbean (LAC) Region (
These challenges are further compounded by the effects of the climatic emergency, which intensifies the vulnerability of urban rivers (
Consequently, many urban rivers have become degraded and at risk, with consequences not only for their ecological dimensions, but also for the quality of life of residents. The loss of ecosystem services and anthropogenic pressures generate various negative impacts, such as areas perceived as unpleasant and unsafe due to the presence of waste, unpleasant odours, lack of lighting, fear of crime and inadequate infrastructure, amongst other aspects that affect people's well-being. These aspects have been studied as ecosystem disservices (
For this reason, several researchers emphasise the need to focus attention on the social values and importance that a local community assigns to a given landscape and its ES (
Therefore, a closer look at the socio-cultural valuation of ES and the landscape provides a crucial perspective to identify and recognise social preferences and areas of particular interest to the community. In the context of altered and degraded ecosystems, these perceptions can have positive or negative connotations. Thus, considering diverse ecosystem values expands the possibilities to identify opportunities and conflicts in the same territory (
In this sense, participatory mapping has been applied as an effective tool to collect data from multiple social agents and integrate it with ecological information to reveal socio-environmental relationships and their spatial association (
This research aims to assess and map the socio-cultural, non-monetary, positive and negative values of the Zamora and Malacatos Rivers and the ES, in their course through the urban-rural gradient in Loja City, Ecuador. With this, it is possible to identify and know the relative importance of the social value and identify its explicit spatial distribution, patterns and ES hotspot from the mapped preferences.
Finally, this research achieves several contributions: (1) It provides an ES case study in a city from the Global South, in a field where most studies have focused on landscapes and social values within the Global North (
The findings offer valuable insights into stakeholder preferences for the riverscape, thereby facilitating their incorporation into planning and management processes.
The Zamora and Malacatos Rivers cohabit with the City of Loja, which is located in the south of the Republic of Ecuador, at 2,100 m a.s.l., with an area of 285.7 km² and a population of 214,855 inhabitants (
Case study: Malacatos and Zamora Rivers in Ecuador. Own elaboration.
a: At the top, the position of the Province of Loja in Ecuador. At the bottom, the City of Loja (black) and the Canton of Loja (light-blue), within the Province of Loja.
b: Situation of the rivers within the study area. Some emblematic places of the city are identified with numbers.
Loja, like many Andean cities in Ecuador, has presented an urban development indifferent to its bodies of water (
In recent decades, the urban growth of Loja has been sustained at an accelerated rate. According to the Ministry of Urban Development and Housing, Loja recorded one of the highest growth rates in the country, reaching 82% (
These are several reasons why there has been a growing interest in studies that seek to assess the ecological integrity of water bodies (
Details of the Zamora and Malacatos Rivers can be seen in Fig.
The data collection was carried out in 2021 in Loja (field visit), with the dissemination of a web-based questionnaire (named OpinaRíos), prepared under the ArcGIS Survey123 Connect (
The survey used a multiple-response format on a Likert scale, divided into different blocks, one part intended to collect information and socio-demographic characteristics and another focused on the degree of satisfaction regarding the state of the rivers, type of relationship and activities carried out on the riverbanks. Finally, the respondents were asked to interact with a map of the city and locate the places with Positive Social Value (PSV) and Negative Social Value (NSV) for the Zamora and Malacatos Rivers and to map the social values. In a last step, participants were asked to assign one to three categories for the PSV and one to three categories for the NSV, to each location, based on a predefined list. (Table
Classification and definition of positive and negative values adapted from
Social Values |
Assigned Value |
Description |
Positive Social Values (PSV) |
Aesthetic |
Sites of particular aesthetic/scenic beauty, sights, sounds or smells. |
Learning |
Sites that widen knowledge about the environment, plant and animal species. |
|
Life sustaining |
It helps produce, preserve, clean and renew the air, soil and water. |
|
Recreation |
Sites used for my favourite outdoor recreation activities. |
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Therapeutic |
It makes me feel better, physically and/or mentally. |
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Negative Social Values (NSV) |
Flood threat |
Sites are perceived to have a flood threat. |
Unpleasantness |
Sites that are neglected, abused, damaged or unpleasant, smelly places. |
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Unsafe, delinquency & harassment |
Sites that feel dangerous or where anti-social events. |
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Little aesthetic value & lack of vegetation |
Sites without vegetation. |
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Poor infrastructure & inaccessible |
Sites with difficult pedestrian access, without furniture. |
Ten categories of landscape´s social value and their ES were used: five corresponding to PSV, such as Aesthetic, Learning, Recreation and typologies used in similar studies (
For this study, the following biophysical variables were used: elevation, land use and land cover (LULC), slope and landscape type, which are metrics commonly adopted in similar studies (
Description and sources of the biophysical and socio-environmental variables used, adapted from
Abbreviations: Ecuadorian Space Institute (IEE), Geographic Military Institute (IGM), Digital Elevation Model (DEM), Phased Array type L-band Synthetic Aperture Radar (PALSAR), Environmental Rasters (ENV_LAYERS).
Name |
Format |
Description |
Source |
Observations |
VALUE_TYPES |
Table |
Types of social values: PSV and NSV |
Predefined |
Aesthetic, learning, Unpleasantness etc. |
STUDY_AREA |
Vector |
Digitised study area based on rivers |
Own elaboration |
Format = shp Type = polygon |
SURVEY_POINTS |
Vector |
Social values geospatialised by survey |
On-site survey Survey123 |
Format = shp Type = point |
ENV_LAYERS |
Table |
Raster type determination |
Predefined |
Variables: Continuous = 0 Categorical = 1 |
LULC |
Raster |
Current use and land cover, 24 classes |
IEE (current IGM) |
Source data: Format = gdb Type = polygon Scale = 25 k |
LANDFORM |
Raster |
Terrain morphology, 11 classes |
IEE (current IGM) |
Source data: Format = gdb Type = polygon Scale = 25 k |
DTGA |
Raster |
Euclidean distance based on green areas |
Municipality of Loja |
Source data: Format = shp Type = polygon |
ELEV |
Raster |
Digital elevation model (DEM) in masl |
ALOS PALSAR |
Format = tiff Pixel = 12.5 m |
SLOPE |
Raster |
Slope map |
ALOS PALSAR DEM |
Format = tiff pixel = 12.5 m |
The Social Values for Ecosystem Services (SolVES 4.0) is a tool utilised for assessing and mapping the social values associated with ecosystem services. It integrates data from two sources, participatory surveys (ten social values: PSV and NSV, Table
Flowchart of the methodology. Numerical labels (1) and (2) represent the sources of the input data: (1) Spatial data and (2) PPGIS survey data. Own elaboration, adapted from
SolVES integrates Geographic Information Systems (GIS) with a Public Participation approach (PPGIS), (https://www.usgs.gov/centers/geosciences-and-environmental-change-science-center/science/social-values-ecosystem). SolVES is an open-source QGIS plug-in developed by the Center for Environmental Change Sciences and Geosciences of the US Geological Survey (USGS) (Denver, CO, USA). To the authors' knowledge, SolVES has not been implemented before in urban landscapes in the LAC Region.
SolVES tool calculated a 'Value Index' (VI) which corresponds to a non-monetary metric that quantifies the social value of the ES on a 10-point scale (
SolVES integrates the maximum entropy model (Maxent), which was originally developed to model the geographic distribution of species, but was adapted to map the social values of ES (
With the results calculated by Maxent, maps were created, that spatially indicated the probability of the attendance of multiple social values of ecosystem services in both rivers. These maps also consider landscape characteristics.
Maxent also produces additional statistics that allow us to describe the performance of generated models. One of them is the "Area Under the Curve" (AUC), which considers the total area under a "Receiver Operating Characteristic" curve (ROC), for the training (75%) and test (25%) data. To consider whether the model has predictive potential, the recommendations of
The tool used by Maxent to determine the contribution of each variable studied is the implementation of the Jackknife test. The percentage contribution (Con) of each variable corresponds to the sum of the gain of including them within each iteration of the training algorithm. The importance of the permutation (Imp) represents the contribution of each variable when considered individually after generating the final model. Both are calculated as percentages (
With this process, integrated raster data were obtained that allows visualising the results on maps. Graphic and tabular reports were obtained for each of the ten mapped social values.
A sample consisting of 200 participants aged between 18 and 70 years was registered. A total of 662 geographical points (representing social values) were obtained, of which 267 correspond to places of "Positive Value" and 381 to places of "Negative Value". The participation of those surveyed registered 44 % women and 53 % men. The age groups with the highest participation are those between 40 - 65 years old (39.5%) and 25 - 40 years old (34%). Regarding the landscape of the rivers, 47% of the participants qualified the landscape of the Malacatos River as "Bad" and, as "Regular", 43.5%, the landscape of the Zamora River (Fig.
The results obtained are summarised in Table
Results of statistical values of the SolVES model, R-ratio (R < 1), Z Score, Training AUC, Test AUC and Maximum Value Index.
Boldface values indicate better results. Abbreviations: Positive Social Values (PSV), Negative Social Values (NSV), Area Under the Curve (AUC), Value Index (VI).
Social Values |
Count # |
Nearest Neighbour Analysis |
AUC |
Max-VI |
|||
R-ratio |
Z-score |
Training |
Test |
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PSV |
Learning |
40 |
0.53 |
-5.7 |
0.93 |
0.82 |
7 |
Aesthetic |
76 |
0.32 |
-11.3 |
0.9 |
0.85 |
6 |
|
Therapeutic |
50 |
0.38 |
-8.4 |
0.89 |
0.87 |
5 |
|
Recreation |
55 |
0.42 |
-8.2 |
0.93 |
0.73 |
5 |
|
Life sustaining |
46 |
0.49 |
-6.7 |
0.87 |
0.77 |
5 |
|
NSV |
Unpleasantness |
121 |
0.44 |
-11.7 |
0.93 |
0.96 |
10 |
Poor infrastructure & inaccessible |
73 |
0.44 |
-9.1 |
0.95 |
0.94 |
9 |
|
Flood threat |
79 |
0.47 |
-9 |
0.95 |
0.98 |
8 |
|
Unsafe, delinquency & harassment |
63 |
0.49 |
-7.7 |
0.96 |
0.95 |
8 |
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Little aesthetic value & lack of vegetation |
45 |
0.53 |
-6 |
0.96 |
0.94 |
7 |
In the first phase, we obtain the distribution of social values, based on the locations mapped by the respondents, most of them spread along the rivers. In this regard, the results of the nearest-neighbour spatial statistics, generated by SolVES, show that the geographical distribution of these points was not random, since statistically significant grouping patterns were identified, given that all R-ratios are < 1 with very negative Z-scores (
Regarding the AUC, to measure the performance and predictive capacity, the model yielded values > 0.9 for most cases, which indicates that it has a good fit for the study area, in addition to the fact that the AUC Test indicates that the model has a useful predictive capacity to transfer social values to other environments (
Finally, the Maximum Value Index (Max-VI) scores for the two subgroups ranged from 5 to 10. A higher Max-VI indicates stronger interest. In this case, the highest indices are found within the NSV, with “Unpleasantness” being the highest (Max-VI = 10) and it also registers the largest number of mapped points (n = 121).
We identify that, for the PSV, the classification in descending order is Learning, Aesthetic, Therapeutic, Recreation and Life-Sustaining. In the case of the NSVs, the descending order is Unpleasantness, Poor Infrastructure & Inaccessible, Flood Threat, Unsafe, Delinquency & Harassment and Little Aesthetic Value & Lack of Vegetation.
To interpret the relative importance and relationship of the biophysical variables used in the model, the percentage of contribution (Con) and the percentage of importance of the permutation (Imp) calculated by Maxent were considered. The Distance To Green Areas (DTGA) variable was the most significant contributor, with a percentage between 34 - 63% and with the importance of permutation of 26 - 57% being, in both cases, the highest values for all the social values.
For "Poor infrastructure & inaccessible" and "Flood threat" 40% and 37%, respectively in permutation importance were obtained with the ELEV variable and "Poor infrastructure & inaccessible" with 31% in permutation importance with the SLOPE variable. (Table
Summary of the environmental variable percentage contribution (Con) and the importance of the permutation (Imp) for each social value (Jackknife test).
Abbreviations: Positive Social Values (PSV), Negative Social Values (NSV), Contribution (Con), Importance (Imp), Elevation (ELEV), Land Use and Land Cover (LULC), horizontal Distance To Green Areas (DTGA).
SOCIAL VALUES |
ELEV |
LANDFORM |
LULC |
SLOPE |
DTGA |
||||||
% Con |
% Imp |
% Con |
% Imp |
% Con |
% Imp |
% Con |
% Imp |
% Con |
% Imp |
||
PSV |
Learning |
7 |
19 |
20 |
16 |
7 |
11 |
8 |
7 |
59 |
47 |
Aesthetic |
8 |
33 |
1 |
3 |
5 |
6 |
25 |
11 |
60 |
48 |
|
Therapeutic |
3 |
9 |
7 |
16 |
14 |
18 |
17 |
6 |
59 |
50 |
|
Recreation |
7 |
14 |
8 |
11 |
7 |
9 |
15 |
10 |
63 |
57 |
|
Life sustaining |
8 |
18 |
15 |
12 |
7 |
13 |
12 |
12 |
58 |
45 |
|
NSV |
Unpleasantness |
12 |
37 |
4 |
4 |
4 |
1 |
35 |
31 |
45 |
26 |
Poor infrastructure & inaccessible |
25 |
34 |
15 |
7 |
2 |
1 |
24 |
23 |
34 |
35 |
|
Flood threat |
16 |
17 |
4 |
4 |
6 |
4 |
27 |
22 |
47 |
52 |
|
Unsafe, delinquency & harassment |
21 |
40 |
5 |
7 |
4 |
1 |
21 |
16 |
48 |
35 |
|
Little aesthetic value & lack of vegetation |
16 |
36 |
8 |
6 |
3 |
1 |
22 |
16 |
51 |
41 |
The resulting maps are the product of analysing the statistics obtained from SolVES, considering the distribution of maximum entropy and evaluating the social values in conjunction with the biophysical values. The maps, both PSV and NSV, can be seen in Fig.
Spatial distribution of Positive Social Values (PSV). Social Values: (a) Learning, (b) Aesthetic, (c) Therapeutic, (d) Recreation, (e) Life-Sustaining.
Spatial distribution of Negative Social Values (NSV), Higher Max-VI represent high negative SV. Social Values: (a) Unpleasantness, (b) Poor Infrastructure & Inaccessible, (c) Flood threat, (d) Unsafe, delinquency & harassment, (e) Little aesthetic value & lack of vegetation.
The generated value index maps display the spatial distribution and serve as a visual representation of the calculated Max-VI, indicating its range and distribution across the entire city. Warm colours are used to denote the highest values of the value index (VI).
Positive Social Values (PSV)
The cartographic results for the five PSV types of the ES generally exhibited a wide distribution throughout the urban river landscape, which influenced the delineation of the study area. Clusters corresponding to high positive scores were observed in certain peripheral areas and the city centre. In terms of spatial distribution, relatively similar patterns were found for the values of Aesthetics, Therapy and Sustainability of Life, especially in the distribution of their lowest values, whereas Recreation and Learning exhibited different distributions as they did not demonstrate concentration patterns, but rather were more dispersed. The latter case, Learning, displayed the highest PSV (7/10) (Table
Negative Social Values (NSV)
The five negative values mapped appeared in the centre area of the city, around the area of confluence of the rivers, which was mainly evidenced in the Unpleasantness map (Fig.
Based on participatory mapping in combination with biophysical data from Loja City, we generated spatially-explicit indicators of social value for each ES and disservice studied.
In general, we found that the ten social values studied received a variety of scores (Table
Specific scores and spatial patterns were also revealed for the ESs studied, where mapping negative values indicate that locations closer to the city centre were more strongly chosen compared to places further away. Hence, they were clustered in a smaller section, while the positive hotspots showed greater dispersion.
In addition, a total of 381 location points for NSV and 267 for PSV were collected for the survey (Table
Concerning PSV maps, we observed similar patterns with an emphasis on Aesthetic and Recreation values. Previous research suggested these two Social Values are important indicators of how people connect with nature (
"Learning" corresponds to the highest PSV (7/10) (Table
The most valued places mapped were in peripheral areas, but in a scattered way, covering a larger area of the city. Therefore, these hotspots should be considered priority intervention areas due to their ability to provide ES and contribute to the well-being of the community (
The "El Carmen" peripheral neighbourhood was one of them; it corresponds to a territory close to the rural sector that appears on most PSV maps (Fig.
In all SVs maps, we notice how the rivers and the surroundings of the parks and squares were outlined by the intensity and the grouping of the points. The previous statement is evident in the areas with a high-Value Index, which appeared very close to green areas of the city, such as: “Zamora Huayco” Linear Park, “La Tebaida” Linear Park, “Jipir” Recreational Park and Zoo. These places are likely to have less anthropogenic conditions that support the sense of place, as well as offer recreational opportunities (
The importance of considering the role of green areas in perceptions of the urban ecosystem is not only because they provide benefits, but also because their uneven distribution can affect the provision of ES throughout the city, increasing spatial injustice.
Regarding the sites where the spatial distribution of locations with high PSV and high NSV coincides, we found that the urban centre, in general, obtained a high representation in all result maps. The main area of spatial clustering was located at the architectural landmark called 'Puerta de la Ciudad' (City Gate) (Fig.
However, around this ''Puerta de la Ciudad'' landmark, the area with the highest urban density is established, making it a highly frequented public place by its inhabitants. For this reason, it can evoke a high sense of historical, heritage and educative significance at the same time as feelings of concern (
The findings of our study offer useful information to identify and establish priority areas for intervention concerning the conditions of the riverscape, where the most valued places can be considered a high priority due to their ability to provide benefits to citizens and represent significant places. In contrast, the negative places need to be recovered. The highest values in both types of ES also deserve special attention; for example, the social value of "learning" highlights the community's interest in environmental education spaces and activities centred around rivers. Conversely, the perception of "unpleasantness" towards the rivers emphasises the urgent need to restore and improve their aesthetic and environmental quality, aspects that urban planners should consider. Excessive anthropogenisation has significantly impacted the natural landscape value of the rivers, which is missed and needed by the community.
Challenges and Opportunities
The mapping methodology focused on PPGIS used in this study employed a web-based survey, ESRI Survey123, which was disseminated in situ through a QR code and URL distribution, to capture social preferences of the landscape and georeference them in real-time, without depending on the place and time, thus avoiding the manual digitisation process of data points. It proved to be a user-friendly platform, reaching the 40 - 65 age group as the most participatory. However, surveyors needed to have a good knowledge of the city and the ability to locate places on a map.
SolVES and Maxent tools were successfully used to analyse, quantify and map the social value of ESs and our study demonstrated the utility and flexibility of PPGIS, capturing tangible and intangible insights and facilitating the provision of indices and maps that can provide information for landscape planning and management processes. To the authors' knowledge, this corresponds to the first application of the SolVES model in Ecuador and the third in the LAC region. Furthermore, their portability as open-source software is noteworthy. However, these tools require advanced technical knowledge and detailed cartographic information of the study area (vectorial and raster). These aspects could limit their application in contexts where technical and human resources are limited. Our study demonstrated the utility and flexibility of Public Participation GIS for capturing tangible and intangible information and facilitating the provision of indices and maps that can provide information for landscape planning.
On the other hand, the application of urban ecosystem services mapping, based on social valuation, promotes a participatory approach to the management and planning of socio-ecological landscapes. This approach establishes a dialogue with the local community to understand their perception and interaction with the river landscape, as well as to identify places of perceived importance. This information can be complemented by evaluations focused on the material and monetary services of the ecosystem, as well as with expert opinions (Villa et al. 2014); in this way, it is possible to obtain an integral evaluation.
This study assessed and mapped the socio-cultural, non-monetary, positive and negative values of the rivers and their ES in Loja City, Ecuador. The metrics, indices and cartographies obtained contributed to the development of a pluralism of values by representing socio-cultural preferences, recognising the multiple benefits and disservices offered by the fluvial urban landscape and mapping areas with a greater or lesser supply of ES, providing a useful guide to sustainability landscape planning. The latter suggests that social values play an essential role in drawing new structural and subjective routes in managing and planning degraded urban rivers. It is validated since it directly recognises how and where the community perceives the ESs landscape, facilitating local knowledge integration towards informed management and decision acceptance. In this respect, we encourage researchers and decision-makers to pay more attention to the role of social assessment in the framework of ES, emphasising the global south, where information is insufficient and pressures on the urban riverscape will continue to increase.
We appreciate all the respondents who shared their perspectives in support of this research. Thanks to Benson Sherrouse (USGS) for his help.
Conceptualisation, methodology, software, investigation, writing—original draft preparation, writing—review and editing, N.A.A., V.M.A. and F.C.T.; validation, resources, data curation, supervision, project administration, funding acquisition, N.A.A. and V.M.A.; formal analysis, visualisation, N.A.A., V.M.A. and F.C.T; N.A.A., V.M.A., F.C.T and A.M.E. resources. All authors have read and agreed to the published version of the manuscript.