Archive | 2019

Learning Landscape Approach Through Evaluation: Opportunities for Pan-European Long-Term Socio-Ecological Research



Sustainable development as a societal process aimed at securing sustainability is challenging. To encourage the necessary knowledge production and learning in different social-ecological contexts requires a place-based networking research infrastructure that involves multiple academic disciplines and non-academic actors. Long-term socio-ecological research (LTSER) platform is one approach with ~80 initiatives globally. To encourage transdisciplinary learning through evaluation we defined a normative model for ideal performance at both local platform and network levels. Four surveys were then sent out to 67 self-reported LTSER platforms. Focusing on the network level, we analyzed the spatial distribution of both long-term ecological monitoring sites within LTSER platforms, and LTSER platforms across the European continent. Finally, narrative biographies about 18 LTSER platforms in different stages of development were analyzed. While the siting of LTSER platforms represented biogeographical regions well, variations in land-use history and governance arrangements were poorly represented. Ecosystem research (72%) dominated social system research (28%). Maintenance of a platform required 3–5 staff members, was based mainly on national funding and had 1–2 years of future funding secured. Networking with other landscape approach concepts was common. Individually, and as a network, LTSER platforms have good potential for transdisciplinary knowledge production and learning about sustainability challenges. To benefit from the large range of variation among Pan-European social-ecological systems, we encourage collaboration among different landscape approach concepts such as LTSER platform and Model Forest, ecological reference landscapes like zapovedniks as well as traditional systems for landscape stewardship.

Volume None
Pages 303-319
DOI 10.1007/978-3-030-30069-2_12
Language English
Journal None

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