There are several spatial valuation and ecosystem service mapping studies using participatory methods in North America, Australia, Europe and Japan. But, there is much less information from urban areas in the Global South using these approaches, particularly regarding the influence of spatial literacy on such methods. Accordingly, we tested how two-dimensional (2D) maps and three-dimensional models (3DCM) influence the identification of urban and peri-urban ecosystem services by different stakeholders near forested landscapes adjacent to Bogotá, Colombia. We used on-site interviews, quantitative machine-learning statistics, and qualitative methods to identify predictors and assess the ability of different stakeholders to identify: peri-urban forest ecosystem services, threats to forest ecosystems, and in locating points of interest. We found that age, residential proximity to the study sites, and education were the best predictors for estimating the number of ecosystem services. Older and non-local interviewees less than 20 years old recognized a greater number of ecosystem services. Using 2D maps to locate predesignated sites resulted in better results than when using a 3DCM; particularly with younger respondents. However, respondents were able to locate more predesignated sites with the 3DCM when they had a higher level of education. As opposed to other studies, our stakeholders more frequently identified regulating as opposed to cultural ecosystem services. Our study identified socio-demographic predictors that could be used to assess different stakeholder’s abilities in recognizing different processes from landscapes as well as their difficulty in accurately locating areas of interest. Such low cost and participatory approaches can be used to design more context-relevant survey instruments for ecosystem service valuation research and assessments.

中文翻译：

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空间素养会影响利益相关者对郊区和城市生态系统服务的认识和定位

在北美，澳大利亚，欧洲和日本，有几种使用参与性方法进行的空间评估和生态系统服务制图研究。但是，使用这些方法从全球南部城市地区获得的信息要少得多，特别是关于空间素养对此类方法的影响。因此，我们测试了二维（2D）地图和三维模型（3DCM）如何影响哥伦比亚波哥大附近森林景观附近的不同利益相关者对城市和近郊生态系统服务的识别。我们使用了现场访谈，定量的机器学习统计数据和定性方法来识别预测因素，并评估不同利益相关者的识别能力：城郊森林生态系统服务，对森林生态系统的威胁以及关注点的定位。我们发现年龄，居住地点与研究地点的距离以及教育程度是估计生态系统服务数量的最佳预测指标。年龄小于20岁的年长者和非本地受访者认识到更多的生态系统服务。与使用3DCM相比，使用2D地图定位预先指定的地点可获得更好的结果；特别是对于年轻的受访者。但是，当受教育者的教育水平较高时，他们可以使用3DCM查找更多预先指定的站点。与其他研究相反，我们的利益相关者更经常地将监管与文化生态系统服务相对比。我们的研究确定了可用于评估不同利益相关者从景观中识别不同过程的能力以及准确定位感兴趣区域的难度的社会人口统计学预测因子。这种低成本和参与性方法可用于设计更多与情境相关的调查工具，用于生态系统服务价值研究和评估。