Ecosystem services for connecting actors - lessons from a symposium

This paper is a communication from the corresponding symposium at the Global Land Project Open Science Meeting, Berlin, March 2014. We explored the assumption that the ecosystem services-(ES) concept has the potential to support communication and collaboration between actors in land use planning. If true, the concept could facilitate collaborative planning processes. We analyse how to evolve a planning context in which governance networks at the local landscape level gain importance in decision making, while the central government delegates power. From case studies presented during the symposium we learned that the ES-concept has been explored for application in local land use planning around the world. However, whether ES are recognized as a useful planning concept depends on individual actor preferences and cultural and contextual factors, such as the actual nature-human relationship and gender differences. Also, successful application requires the support of novel assessment, design and visualization tools, which are designed to foster collaboration and social learning. The potential of the concept to contribute to collaborative relationships needs further investigation

Linking model design and application for transdisciplinary approaches in social-ecological systems

This work was supported by the US National Science Foundation through the Mountain Sentinels Research Coordination Network (NSF #1414106), the Swiss National Science Foundation through MtnPaths – Pathways for global change adaptation of mountain socio-ecological systems (#20521L_169916), and the Center for Collaborative Conservation at Colorado State University.As global environmental change continues to accelerate and intensify, science and society are turning to trans- disciplinary approaches to facilitate transitions to sustainability. Modeling is increasingly used as a technological tool to improve our understanding of social-ecological systems (SES), encourage collaboration and learning, and facilitate decision-making. This study improves our understanding of how SES models are designed and applied to address the rising challenges of global environmental change, using mountains as a representative system. We analyzed 74 peer-reviewed papers describing dynamic models of mountain SES, evaluating them according to characteristics such as the model purpose, data and model type, level of stakeholder involvement, and spatial extent/resolution. Slightly more than half the models in our analysis were participatory, yet only 21.6% of papers demonstrated any direct outreach to decision makers. We found that SES models tend to under-represent social datasets, with ethnographic data rarely incorporated. Modeling efforts in conditions of higher stakeholder diversity tend to have higher rates of decision support compared to situations where stakeholder diversity is absent or not addressed. We discuss our results through the lens of appropriate technology, drawing on the concepts of boundary objects and scalar devices from Science and Technology Studies. We propose four guiding principles to facilitate the development of SES models as appropriate technology for transdisciplinary applications: (1) increase diversity of stakeholders in SES model design and application for improved collaboration; (2) balance power dynamics among stakeholders by incorporating diverse knowledge and data types; (3) promote flexibility in model design; and (4) bridge gaps in decision support, learning, and communication. Creating SES models that are appropriate tech- nology for transdisciplinary applications will require advanced planning, increased funding for and attention to the role of diverse data and knowledge, and stronger partnerships across disciplinary divides. Highly contextualized participatory modeling that embraces diversity in both data and actors appears poised to make strong contributions to the world’s most pressing environmental challenges.PostprintPeer reviewe

Predicting the scenic beauty value of mapped landscape changes in a mountainous region through the use of GIS

C1 - Journal Articles Referee

An improved neutral landscape model for recreating real landscapes and generating landscape series for spatial ecological simulations

Many studies have assessed the effect of landscape patterns on spatial ecological processes by simulating these processes in computer-generated landscapes with varying composition and configuration. To generate such landscapes, various neutral landscape models have been developed. However, the limited set of landscape-level pattern variables included in these models is often inadequate to generate landscapes that reflect real landscapes. In order to achieve more flexibility and variability in the generated landscapes patterns, a more complete set of class- and patch-level pattern variables should be implemented in these models. These enhancements have been implemented in Landscape Generator (LG), which is a software that uses optimization algorithms to generate landscapes that match user-defined target values. Developed for participatory spatial planning at small scale, we enhanced the usability of LG and demonstrated how it can be used for larger scale ecological studies. First, we used LG to recreate landscape patterns from a real landscape (i.e., a mountainous region in Switzerland). Second, we generated landscape series with incrementally changing pattern variables, which could be used in ecological simulation studies. We found that LG was able to recreate landscape patterns that approximate those of real landscapes. Furthermore, we successfully generated landscape series that would not have been possible with traditional neutral landscape models. LG is a promising novel approach for generating neutral landscapes and enables testing of new hypotheses regarding the influence of landscape patterns on ecological processes. LG is freely available online

An improved neutral landscape model for recreating real landscapes and generating landscape series for spatial ecological simulations

Many studies have assessed the effect of landscape patterns on spatial ecological processes by simulating these processes in computer-generated landscapes with varying composition and configuration. To generate such landscapes, various neutral landscape models have been developed. However, the limited set of landscape-level pattern variables included in these models is often inadequate to generate landscapes that reflect real landscapes. In order to achieve more flexibility and variability in the generated landscapes patterns, a more complete set of class- and patch-level pattern variables should be implemented in these models. These enhancements have been implemented in Landscape Generator (LG), which is a software that uses optimization algorithms to generate landscapes that match user-defined target values. Developed for participatory spatial planning at small scale, we enhanced the usability of LG and demonstrated how it can be used for larger scale ecological studies. First, we used LG to recreate landscape patterns from a real landscape (i.e., a mountainous region in Switzerland). Second, we generated landscape series with incrementally changing pattern variables, which could be used in ecological simulation studies. We found that LG was able to recreate landscape patterns that approximate those of real landscapes. Furthermore, we successfully generated landscape series that would not have been possible with traditional neutral landscape models. LG is a promising novel approach for generating neutral landscapes and enables testing of new hypotheses regarding the influence of landscape patterns on ecological processes. LG is freely available online

Identification of practically visible spatial objects in natural environments

Image retrieval of landscape photographs requires accurate annotation using multi-faceted descriptions relating to the subject and content of the photograph. The subject of such photographs is dominantly the terrain and spatial objects visible from the photographer’s viewpoint. While some spatial objects in the background may be obscured by foreground vegetation, other visible spatial objects beyond a certain distance may not present noteworthy elements of the captured scene (such as distant houses). Our aim is to assess approaches to improve the identification of practically visible spatial objects for image annotation. These approaches include the consideration of the apparent spatial object size and landcover information about occluding vegetation. These inputs are used to enhance viewshed analysis to accurately identify only spatial objects practically visible and therefore likely to be notable subjects of a photograph. The two approaches are evaluated in an experiment in a semi-rural area of Switzerland, whose results indicate that visual magnitude is key in accurate identification of visible spatial objects

Contributions of Cultural Services to the Ecosystem Services Agenda

Cultural ecosystem services (ES) are consistently recognized but not yet adequately defined or integrated within the ES framework. A substantial body of models, methods, and data relevant to cultural services has been developed within the social and behavioral sciences before and outside of the ES approach. A selective review of work in landscape aesthetics, cultural heritage, outdoor recreation, and spiritual significance demonstrates opportunities for operationally defining cultural services in terms of socioecological models, consistent with the larger set of ES. Such models explicitly link ecological structures and functions with cultural values and benefits, facilitating communication between scientists and stakeholders and enabling economic, multicriterion, deliberative evaluation and other methods that can clarify tradeoffs and synergies involving cultural ES. Based on this approach, a common representation is offered that frames cultural services, along with all ES, by the relative contribution of relevant ecological structures and functions and by applicable social evaluation approaches. This perspective provides a foundation for merging ecological and social science epistemologies to define and integrate cultural services better within the broader ES framework