Search

Landscape planning has been advocated by many researchers and conservationists because of its potential to support nature conservation at broad spatial scales. We examined an internationally funded project in Vietnam (the ECOLIME project) that failed in its endeavor to establish landscape planning at the scale of an ecologically valuable karst landscape. We applied the Research–Integration–Utilization model of scientific knowledge transfer to analyze why the ECOLIME project did not succeed in adapting the scale of the political–administrative planning system to the ecological scale of the karst ecosystem landscape. Our study shows that the implementation of landscape planning in the Pu-Luong Cuc Phuong area was not successful to solve scale mismatches in environmental governance because of weak integration, resulting from both the absence of a link to the Vietnamese political process and the lack of support from powerful Vietnamese actors. The establishment of a landscape planning group with the support of an internationally funded project (the ECOLIME project) was not a sufficient means to create links to the political process and win powerful allies. Based on the results of this study, we recommend improvements in integration to make scientific research relevant to science-based policy support, including (1) the need for a link to the existing political process and (2) the need to gain sustainable support from powerful allies.

The transfer of scientific knowledge has received great attention by scientists and policymakers especially in fields that are crucially dependent on scientific knowledge like biodiversity conservation or climate change. Although many efforts have been made to better understand how scientific expertise can have an impact on politics, few studies have investigated the influence of limiting factors on scientific knowledge transfer. In this paper, we use a meta-analysis of 13 existing individual case studies from 5 different countries that all have in common that they apply the Research–Integration–Utilization model (the RIU model) to analyze limits of scientific knowledge transfer within research, integration, and utilization. Our results show that the factors of research, integration, and utilization are independent from each other in limiting or increasing the transfer of scientific knowledge. The independence of the RIU's factors also reveals that the increase of scientific knowledge alone will not lead to an improvement in knowledge transfer. There is empirical evidence in our cases providing that utilization could also be possible without a strong scientific basis, and successful integration could be based on weak scientific grounds. As a result of the independence of the different factors the RIU model consists of, the traps of scientific knowledge transfer could be observed in one or multiple RIU's factors and therefore improvements in scientific knowledge transfer should be orientated toward solely one or multiple factors instead of the whole process. We recommend that single improvements of different individual factors (research, integration, utilization) can help to improve the whole process of scientific knowledge transfer.